GenCLiP 2.0: a web server for functional clustering of genes and construction of molecular networks based on free terms.

PubMed

Wang, Jia-Hong; Zhao, Ling-Feng; Lin, Pei; Su, Xiao-Rong; Chen, Shi-Jun; Huang, Li-Qiang; Wang, Hua-Feng; Zhang, Hai; Hu, Zhen-Fu; Yao, Kai-Tai; Huang, Zhong-Xi

2014-09-01

Identifying biological functions and molecular networks in a gene list and how the genes may relate to various topics is of considerable value to biomedical researchers. Here, we present a web-based text-mining server, GenCLiP 2.0, which can analyze human genes with enriched keywords and molecular interactions. Compared with other similar tools, GenCLiP 2.0 offers two unique features: (i) analysis of gene functions with free terms (i.e. any terms in the literature) generated by literature mining or provided by the user and (ii) accurate identification and integration of comprehensive molecular interactions from Medline abstracts, to construct molecular networks and subnetworks related to the free terms. http://ci.smu.edu.cn. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Information networks in the stock market based on the distance of the multi-attribute dimensions between listed companies

NASA Astrophysics Data System (ADS)

Liu, Qian; Li, Huajiao; Liu, Xueyong; Jiang, Meihui

2018-04-01

In the stock market, there are widespread information connections between economic agents. Listed companies can obtain mutual information about investment decisions from common shareholders, and the extent of sharing information often determines the relationships between listed companies. Because different shareholder compositions and investment shares lead to different formations of the company's governance mechanisms, we map the investment relationships between shareholders to the multi-attribute dimensional spaces of the listed companies (each shareholder investment in a company is a company dimension). Then, we construct the listed company's information network based on co-shareholder relationships. The weights for the edges in the information network are measured with the Euclidean distance between the listed companies in the multi-attribute dimension space. We define two indices to analyze the information network's features. We conduct an empirical study that analyzes Chinese listed companies' information networks. The results from the analysis show that with the diversification and decentralization of shareholder investments, almost all Chinese listed companies exchanged information through common shareholder relationships, and there is a gradual reduction in information sharing capacity between listed companies that have common shareholders. This network analysis has benefits for risk management and portfolio investments.

Molecular profiles to biology and pathways: a systems biology approach.

PubMed

Van Laere, Steven; Dirix, Luc; Vermeulen, Peter

2016-06-16

Interpreting molecular profiles in a biological context requires specialized analysis strategies. Initially, lists of relevant genes were screened to identify enriched concepts associated with pathways or specific molecular processes. However, the shortcoming of interpreting gene lists by using predefined sets of genes has resulted in the development of novel methods that heavily rely on network-based concepts. These algorithms have the advantage that they allow a more holistic view of the signaling properties of the condition under study as well as that they are suitable for integrating different data types like gene expression, gene mutation, and even histological parameters.

On the topological properties of the cross-shareholding networks of listed companies in China: Taking shareholders’ cross-shareholding relationships into account

NASA Astrophysics Data System (ADS)

Li, Huajiao; An, Haizhong; Gao, Xiangyun; Huang, Jiachen; Xu, Qun

2014-07-01

Shareholders are the owners of listed companies, and their relationships can directly affect the structure of the stock market. In this paper, we analyze the topological properties and evolution of the cross-shareholding networks of listed companies in the past 5 years in China from 2007 to 2011, an infrequently considered topic, by taking shareholders' cross-shareholding relationships into account. This analysis arrives at a deeper insight into the inner characteristics of China's stock market. We find that the cross-shareholding networks of listed companies with shareholders' cross-shareholding relationships display statistical features that reveal the stock market's complex relationships more precisely. In particular, the results show that when the shareholders' cross-shareholding relationships are considered, first, the In-degree and Out-degree of the cross-shareholding networks follow power-law distribution and the R2 of the linear regression analysis of the cumulative degree distribution is relatively higher; second, the modularity of the communities is larger; finally, both the number of members of top-ranked communities and the number of communities that have a large number of members are larger than those of which only considering the relationships between shareholders and listed companies are taken into account. Such cross-shareholding networks analysis taking shareholders' cross-shareholding relations into account would be a helpful tool for supervisory departments and for stock market researchers to grasp the inner cross-shareholding relationships of listed companies in China, and it will be also helpful for the further researches about the "agent problems" in the stock markets from a whole point of view.

Identification of GRB2 and GAB1 Coexpression as an Unfavorable Prognostic Factor for Hepatocellular Carcinoma by a Combination of Expression Profile and Network Analysis

PubMed Central

Yang, Mei; Wang, Danhua; Yu, Lingxiang; Guo, Chaonan; Guo, Xiaodong; Lin, Na

2013-01-01

Aim To screen novel markers for hepatocellular carcinoma (HCC) by a combination of expression profile, interaction network analysis and clinical validation. Methods HCC significant molecules which are differentially expressed or had genetic variations in HCC tissues were obtained from five existing HCC related databases (OncoDB.HCC, HCC.net, dbHCCvar, EHCO and Liverome). Then, the protein-protein interaction (PPI) network of these molecules was constructed. Three topological features of the network ('Degree', 'Betweenness', and 'Closeness') and the k-core algorithm were used to screen candidate HCC markers which play crucial roles in tumorigenesis of HCC. Furthermore, the clinical significance of two candidate HCC markers growth factor receptor-bound 2 (GRB2) and GRB2-associated-binding protein 1 (GAB1) was validated. Results In total, 6179 HCC significant genes and 977 HCC significant proteins were collected from existing HCC related databases. After network analysis, 331 candidate HCC markers were identified. Especially, GAB1 has the highest k-coreness suggesting its central localization in HCC related network, and the interaction between GRB2 and GAB1 has the largest edge-betweenness implying it may be biologically important to the function of HCC related network. As the results of clinical validation, the expression levels of both GRB2 and GAB1 proteins were significantly higher in HCC tissues than those in their adjacent nonneoplastic tissues. More importantly, the combined GRB2 and GAB1 protein expression was significantly associated with aggressive tumor progression and poor prognosis in patients with HCC. Conclusion This study provided an integrative analysis by combining expression profile and interaction network analysis to identify a list of biologically significant HCC related markers and pathways. Further experimental validation indicated that the aberrant expression of GRB2 and GAB1 proteins may be strongly related to tumor progression and prognosis in patients with HCC. The overexpression of GRB2 in combination with upregulation of GAB1 may be an unfavorable prognostic factor for HCC. PMID:24391994

Seeking unique and common biological themes in multiple gene lists or datasets: pathway pattern extraction pipeline for pathway-level comparative analysis.

PubMed

Yi, Ming; Mudunuri, Uma; Che, Anney; Stephens, Robert M

2009-06-29

One of the challenges in the analysis of microarray data is to integrate and compare the selected (e.g., differential) gene lists from multiple experiments for common or unique underlying biological themes. A common way to approach this problem is to extract common genes from these gene lists and then subject these genes to enrichment analysis to reveal the underlying biology. However, the capacity of this approach is largely restricted by the limited number of common genes shared by datasets from multiple experiments, which could be caused by the complexity of the biological system itself. We now introduce a new Pathway Pattern Extraction Pipeline (PPEP), which extends the existing WPS application by providing a new pathway-level comparative analysis scheme. To facilitate comparing and correlating results from different studies and sources, PPEP contains new interfaces that allow evaluation of the pathway-level enrichment patterns across multiple gene lists. As an exploratory tool, this analysis pipeline may help reveal the underlying biological themes at both the pathway and gene levels. The analysis scheme provided by PPEP begins with multiple gene lists, which may be derived from different studies in terms of the biological contexts, applied technologies, or methodologies. These lists are then subjected to pathway-level comparative analysis for extraction of pathway-level patterns. This analysis pipeline helps to explore the commonality or uniqueness of these lists at the level of pathways or biological processes from different but relevant biological systems using a combination of statistical enrichment measurements, pathway-level pattern extraction, and graphical display of the relationships of genes and their associated pathways as Gene-Term Association Networks (GTANs) within the WPS platform. As a proof of concept, we have used the new method to analyze many datasets from our collaborators as well as some public microarray datasets. This tool provides a new pathway-level analysis scheme for integrative and comparative analysis of data derived from different but relevant systems. The tool is freely available as a Pathway Pattern Extraction Pipeline implemented in our existing software package WPS, which can be obtained at http://www.abcc.ncifcrf.gov/wps/wps_index.php.

Macro-Econophysics

NASA Astrophysics Data System (ADS)

Aoyama, Hideaki; Fujiwara, Yoshi; Ikeda, Yuichi; Iyetomi, Hiroshi; Souma, Wataru; Yoshikawa, Hiroshi

2017-07-01

Preface; Foreword, Acknowledgements, List of tables; List of figures, prologue, 1. Introduction: reconstructing macroeconomics; 2. Basic concepts in statistical physics and stochastic models; 3. Income and firm-size distributions; 4. Productivity distribution and related topics; 5. Multivariate time-series analysis; 6. Business cycles; 7. Price dynamics and inflation/deflation; 8. Complex network, community analysis, visualization; 9. Systemic risks; Appendix A: computer program for beginners; Epilogue; Bibliography; Index.

Integrated workflow for characterizing and modeling fracture network in unconventional reservoirs using microseismic data

NASA Astrophysics Data System (ADS)

Ayatollahy Tafti, Tayeb

We develop a new method for integrating information and data from different sources. We also construct a comprehensive workflow for characterizing and modeling a fracture network in unconventional reservoirs, using microseismic data. The methodology is based on combination of several mathematical and artificial intelligent techniques, including geostatistics, fractal analysis, fuzzy logic, and neural networks. The study contributes to scholarly knowledge base on the characterization and modeling fractured reservoirs in several ways; including a versatile workflow with a novel objective functions. Some the characteristics of the methods are listed below: 1. The new method is an effective fracture characterization procedure estimates different fracture properties. Unlike the existing methods, the new approach is not dependent on the location of events. It is able to integrate all multi-scaled and diverse fracture information from different methodologies. 2. It offers an improved procedure to create compressional and shear velocity models as a preamble for delineating anomalies and map structures of interest and to correlate velocity anomalies with fracture swarms and other reservoir properties of interest. 3. It offers an effective way to obtain the fractal dimension of microseismic events and identify the pattern complexity, connectivity, and mechanism of the created fracture network. 4. It offers an innovative method for monitoring the fracture movement in different stages of stimulation that can be used to optimize the process. 5. Our newly developed MDFN approach allows to create a discrete fracture network model using only microseismic data with potential cost reduction. It also imposes fractal dimension as a constraint on other fracture modeling approaches, which increases the visual similarity between the modeled networks and the real network over the simulated volume.

OmicsNet: a web-based tool for creation and visual analysis of biological networks in 3D space.

PubMed

Zhou, Guangyan; Xia, Jianguo

2018-06-07

Biological networks play increasingly important roles in omics data integration and systems biology. Over the past decade, many excellent tools have been developed to support creation, analysis and visualization of biological networks. However, important limitations remain: most tools are standalone programs, the majority of them focus on protein-protein interaction (PPI) or metabolic networks, and visualizations often suffer from 'hairball' effects when networks become large. To help address these limitations, we developed OmicsNet - a novel web-based tool that allows users to easily create different types of molecular interaction networks and visually explore them in a three-dimensional (3D) space. Users can upload one or multiple lists of molecules of interest (genes/proteins, microRNAs, transcription factors or metabolites) to create and merge different types of biological networks. The 3D network visualization system was implemented using the powerful Web Graphics Library (WebGL) technology that works natively in most major browsers. OmicsNet supports force-directed layout, multi-layered perspective layout, as well as spherical layout to help visualize and navigate complex networks. A rich set of functions have been implemented to allow users to perform coloring, shading, topology analysis, and enrichment analysis. OmicsNet is freely available at http://www.omicsnet.ca.

Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome data.

PubMed

Li, Xiaomei; Dong, Weiwei; Qu, Xueling; Zhao, Huixia; Wang, Shuo; Hao, Yixin; Li, Qiuwen; Zhu, Jianhua; Ye, Min; Xiao, Wenhua

2017-05-01

Gastric cancer (GC) is often diagnosed in the advanced stages and is associated with a poor prognosis. Obtaining an in depth understanding of the molecular mechanisms of GC has lagged behind compared with other cancers. This study aimed to identify candidate biomarkers for GC. An integrated analysis of microarray datasets was performed to identify differentially expressed genes (DEGs) between GC and normal tissues. Gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were then performed to identify the functions of the DEGs. Furthermore, a protein-protein interaction (PPI) network of the DEGs was constructed. The expression levels of the DEGs were validated in human GC tissues using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). A set of 689 DEGs were identified in GC tissues, as compared with normal tissues, including 202 upregulated DEGs and 487 downregulated DEGs. The KEGG pathway analysis suggested that various pathways may play important roles in the pathology of GC, including pathways related to protein digestion and absorption, extracellular matrix-receptor interaction, and the metabolism of xenobiotics by cytochrome P450. The PPI network analysis indicated that the significant hub proteins consisted of SPP1, TOP2A and ARPC1B. RT-qPCR validation indicated that the expression levels of the top 10 most significantly dysexpressed genes were consistent with the illustration of the integrated analysis. The present study yielded a reference list of reliable DEGs, which represents a robust pool of candidates for further evaluation of GC pathogenesis and treatment.

Lynx web services for annotations and systems analysis of multi-gene disorders.

PubMed

Sulakhe, Dinanath; Taylor, Andrew; Balasubramanian, Sandhya; Feng, Bo; Xie, Bingqing; Börnigen, Daniela; Dave, Utpal J; Foster, Ian T; Gilliam, T Conrad; Maltsev, Natalia

2014-07-01

Lynx is a web-based integrated systems biology platform that supports annotation and analysis of experimental data and generation of weighted hypotheses on molecular mechanisms contributing to human phenotypes and disorders of interest. Lynx has integrated multiple classes of biomedical data (genomic, proteomic, pathways, phenotypic, toxicogenomic, contextual and others) from various public databases as well as manually curated data from our group and collaborators (LynxKB). Lynx provides tools for gene list enrichment analysis using multiple functional annotations and network-based gene prioritization. Lynx provides access to the integrated database and the analytical tools via REST based Web Services (http://lynx.ci.uchicago.edu/webservices.html). This comprises data retrieval services for specific functional annotations, services to search across the complete LynxKB (powered by Lucene), and services to access the analytical tools built within the Lynx platform. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Analyzing and interpreting genome data at the network level with ConsensusPathDB.

PubMed

Herwig, Ralf; Hardt, Christopher; Lienhard, Matthias; Kamburov, Atanas

2016-10-01

ConsensusPathDB consists of a comprehensive collection of human (as well as mouse and yeast) molecular interaction data integrated from 32 different public repositories and a web interface featuring a set of computational methods and visualization tools to explore these data. This protocol describes the use of ConsensusPathDB (http://consensuspathdb.org) with respect to the functional and network-based characterization of biomolecules (genes, proteins and metabolites) that are submitted to the system either as a priority list or together with associated experimental data such as RNA-seq. The tool reports interaction network modules, biochemical pathways and functional information that are significantly enriched by the user's input, applying computational methods for statistical over-representation, enrichment and graph analysis. The results of this protocol can be observed within a few minutes, even with genome-wide data. The resulting network associations can be used to interpret high-throughput data mechanistically, to characterize and prioritize biomarkers, to integrate different omics levels, to design follow-up functional assay experiments and to generate topology for kinetic models at different scales.

Desiderata for healthcare integrated data repositories based on architectural comparison of three public repositories.

PubMed

Huser, Vojtech; Cimino, James J

2013-01-01

Integrated data repositories (IDRs) are indispensable tools for numerous biomedical research studies. We compare three large IDRs (Informatics for Integrating Biology and the Bedside (i2b2), HMO Research Network's Virtual Data Warehouse (VDW) and Observational Medical Outcomes Partnership (OMOP) repository) in order to identify common architectural features that enable efficient storage and organization of large amounts of clinical data. We define three high-level classes of underlying data storage models and we analyze each repository using this classification. We look at how a set of sample facts is represented in each repository and conclude with a list of desiderata for IDRs that deal with the information storage model, terminology model, data integration and value-sets management.

Computer codes developed and under development at Lewis

NASA Technical Reports Server (NTRS)

Chamis, Christos C.

1992-01-01

The objective of this summary is to provide a brief description of: (1) codes developed or under development at LeRC; and (2) the development status of IPACS with some typical early results. The computer codes that have been developed and/or are under development at LeRC are listed in the accompanying charts. This list includes: (1) the code acronym; (2) select physics descriptors; (3) current enhancements; and (4) present (9/91) code status with respect to its availability and documentation. The computer codes list is grouped by related functions such as: (1) composite mechanics; (2) composite structures; (3) integrated and 3-D analysis; (4) structural tailoring; and (5) probabilistic structural analysis. These codes provide a broad computational simulation infrastructure (technology base-readiness) for assessing the structural integrity/durability/reliability of propulsion systems. These codes serve two other very important functions: they provide an effective means of technology transfer; and they constitute a depository of corporate memory.

Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

PubMed

Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

2017-01-01

Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

A Standard for Command, Control, Communications and Computers (C4) Test Data Representation to Integrate with High-Performance Data Reduction

DTIC Science & Technology

2015-06-01

events was ad - hoc and problematic due to time constraints and changing requirements. Determining errors in context and heuristics required expertise...area code ) 410-278-4678 Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 iii Contents List of Figures iv 1. Introduction 1...reduction code ...........8 1 1. Introduction Data reduction for analysis of Command, Control, Communications, and Computer (C4) network tests

Integration and the performance of healthcare networks:do integration strategies enhance efficiency, profitability, and image?

PubMed Central

Wan, Thomas T.H.; Ma, Allen; Y.J.Lin, Blossom

2001-01-01

Abstract Purpose This study examines the integration effects on efficiency and financial viability of the top 100 integrated healthcare networks (IHNs) in the United States. Theory A contingency- strategic theory is used to identify the relationship of IHNs' performance to their structural and operational characteristics and integration strategies. Methods The lists of the top 100 IHNs ranked in two years, 1998 and 1999, by the SMG Marketing Group were merged to create a database for the study. Multiple indicators were used to examine the relationship between IHNs' characteristics and their performance in efficiency and financial viability. A path analytical model was developed and validated by the Mplus statistical program. Factors influencing the top 100 IHNs' images, represented by attaining ranking among the top 100 in two consecutive years, were analysed. Results and conclusion No positive associations were found between integration and network performance in efficiency or profits. Longitudinal data are needed to investigate the effect of integration on healthcare networks' financial performance. PMID:16896405

Comparative analysis of protein interactome networks prioritizes candidate genes with cancer signatures.

PubMed

Li, Yongsheng; Sahni, Nidhi; Yi, Song

2016-11-29

Comprehensive understanding of human cancer mechanisms requires the identification of a thorough list of cancer-associated genes, which could serve as biomarkers for diagnoses and therapies in various types of cancer. Although substantial progress has been made in functional studies to uncover genes involved in cancer, these efforts are often time-consuming and costly. Therefore, it remains challenging to comprehensively identify cancer candidate genes. Network-based methods have accelerated this process through the analysis of complex molecular interactions in the cell. However, the extent to which various interactome networks can contribute to prediction of candidate genes responsible for cancer is still enigmatic. In this study, we evaluated different human protein-protein interactome networks and compared their application to cancer gene prioritization. Our results indicate that network analyses can increase the power to identify novel cancer genes. In particular, such predictive power can be enhanced with the use of unbiased systematic protein interaction maps for cancer gene prioritization. Functional analysis reveals that the top ranked genes from network predictions co-occur often with cancer-related terms in literature, and further, these candidate genes are indeed frequently mutated across cancers. Finally, our study suggests that integrating interactome networks with other omics datasets could provide novel insights into cancer-associated genes and underlying molecular mechanisms.

When is hub gene selection better than standard meta-analysis?

PubMed

Langfelder, Peter; Mischel, Paul S; Horvath, Steve

2013-01-01

Since hub nodes have been found to play important roles in many networks, highly connected hub genes are expected to play an important role in biology as well. However, the empirical evidence remains ambiguous. An open question is whether (or when) hub gene selection leads to more meaningful gene lists than a standard statistical analysis based on significance testing when analyzing genomic data sets (e.g., gene expression or DNA methylation data). Here we address this question for the special case when multiple genomic data sets are available. This is of great practical importance since for many research questions multiple data sets are publicly available. In this case, the data analyst can decide between a standard statistical approach (e.g., based on meta-analysis) and a co-expression network analysis approach that selects intramodular hubs in consensus modules. We assess the performance of these two types of approaches according to two criteria. The first criterion evaluates the biological insights gained and is relevant in basic research. The second criterion evaluates the validation success (reproducibility) in independent data sets and often applies in clinical diagnostic or prognostic applications. We compare meta-analysis with consensus network analysis based on weighted correlation network analysis (WGCNA) in three comprehensive and unbiased empirical studies: (1) Finding genes predictive of lung cancer survival, (2) finding methylation markers related to age, and (3) finding mouse genes related to total cholesterol. The results demonstrate that intramodular hub gene status with respect to consensus modules is more useful than a meta-analysis p-value when identifying biologically meaningful gene lists (reflecting criterion 1). However, standard meta-analysis methods perform as good as (if not better than) a consensus network approach in terms of validation success (criterion 2). The article also reports a comparison of meta-analysis techniques applied to gene expression data and presents novel R functions for carrying out consensus network analysis, network based screening, and meta analysis.

Wallops Ship Surveillance System

NASA Technical Reports Server (NTRS)

Smith, Donna C.

2011-01-01

Approved as a Wallops control center backup system, the Wallops Ship Surveillance Software is a day-of-launch risk analysis tool for spaceport activities. The system calculates impact probabilities and displays ship locations relative to boundary lines. It enables rapid analysis of possible flight paths to preclude the need to cancel launches and allow execution of launches in a timely manner. Its design is based on low-cost, large-customer- base elements including personal computers, the Windows operating system, C/C++ object-oriented software, and network interfaces. In conformance with the NASA software safety standard, the system is designed to ensure that it does not falsely report a safe-for-launch condition. To improve the current ship surveillance method, the system is designed to prevent delay of launch under a safe-for-launch condition. A single workstation is designated the controller of the official ship information and the official risk analysis. Copies of this information are shared with other networked workstations. The program design is divided into five subsystems areas: 1. Communication Link -- threads that control the networking of workstations; 2. Contact List -- a thread that controls a list of protected item (ocean vessel) information; 3. Hazard List -- threads that control a list of hazardous item (debris) information and associated risk calculation information; 4. Display -- threads that control operator inputs and screen display outputs; and 5. Archive -- a thread that controls archive file read and write access. Currently, most of the hazard list thread and parts of other threads are being reused as part of a new ship surveillance system, under the SureTrak project.

Inequalities in Global Trade: A Cross-Country Comparison of Trade Network Position, Economic Wealth, Pollution and Mortality.

PubMed

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; Myroniuk, Tyler W

2015-01-01

In this paper we investigate how structural patterns of international trade give rise to emissions inequalities across countries, and how such inequality in turn impact countries' mortality rates. We employ Multi-regional Input-Output analysis to distinguish between sulfur-dioxide (SO2) emissions produced within a country's boarders (production-based emissions) and emissions triggered by consumption in other countries (consumption-based emissions). We use social network analysis to capture countries' level of integration within the global trade network. We then apply the Prais-Winsten panel estimation technique to a panel data set across 172 countries over 20 years (1990-2010) to estimate the relationships between countries' level of integration and SO2 emissions, and the impact of trade integration and SO2 emission on mortality rates. Our findings suggest a positive, (log-) linear relationship between a country's level of integration and both kinds of emissions. In addition, although more integrated countries are mainly responsible for both forms of emissions, our findings indicate that they also tend to experience lower mortality rates. Our approach offers a unique combination of social network analysis with multiregional input-output analysis, which better operationalizes intuitive concepts about global trade and trade structure.

Analysis of Bos taurus and Sus scrofa X and Y chromosome transcriptome highlights reproductive driver genes

PubMed Central

Khan, Faheem Ahmed; Liu, Hui; Zhou, Hao; Wang, Kai; Qamar, Muhammad Tahir Ul; Pandupuspitasari, Nuruliarizki Shinta; Shujun, Zhang

2017-01-01

The biology of sperm, its capability of fertilizing an egg and its role in sex ratio are the major biological questions in reproductive biology. To answer these question we integrated X and Y chromosome transcriptome across different species: Bos taurus and Sus scrofa and identified reproductive driver genes based on Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm. Our strategy resulted in 11007 and 10445 unique genes consisting of 9 and 11 reproductive modules in Bos taurus and Sus scrofa, respectively. The consensus module calculation yields an overall 167 overlapped genes which were mapped to 846 DEGs in Bos taurus to finally get a list of 67 dual feature genes. We develop gene co-expression network of selected 67 genes that consists of 58 nodes (27 down-regulated and 31 up-regulated genes) enriched to 66 GO biological process (BP) including 6 GO annotations related to reproduction and two KEGG pathways. Moreover, we searched significantly related TF (ISRE, AP1FJ, RP58, CREL) and miRNAs (bta-miR-181a, bta-miR-17-5p, bta-miR-146b, bta-miR-146a) which targeted the genes in co-expression network. In addition we performed genetic analysis including phylogenetic, functional domain identification, epigenetic modifications, mutation analysis of the most important reproductive driver genes PRM1, PPP2R2B and PAFAH1B1 and finally performed a protein docking analysis to visualize their therapeutic and gene expression regulation ability. PMID:28903352

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites

PubMed Central

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K.

2018-01-01

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly. PMID:29470400

RaMP: A Comprehensive Relational Database of Metabolomics Pathways for Pathway Enrichment Analysis of Genes and Metabolites.

PubMed

Zhang, Bofei; Hu, Senyang; Baskin, Elizabeth; Patt, Andrew; Siddiqui, Jalal K; Mathé, Ewy A

2018-02-22

The value of metabolomics in translational research is undeniable, and metabolomics data are increasingly generated in large cohorts. The functional interpretation of disease-associated metabolites though is difficult, and the biological mechanisms that underlie cell type or disease-specific metabolomics profiles are oftentimes unknown. To help fully exploit metabolomics data and to aid in its interpretation, analysis of metabolomics data with other complementary omics data, including transcriptomics, is helpful. To facilitate such analyses at a pathway level, we have developed RaMP (Relational database of Metabolomics Pathways), which combines biological pathways from the Kyoto Encyclopedia of Genes and Genomes (KEGG), Reactome, WikiPathways, and the Human Metabolome DataBase (HMDB). To the best of our knowledge, an off-the-shelf, public database that maps genes and metabolites to biochemical/disease pathways and can readily be integrated into other existing software is currently lacking. For consistent and comprehensive analysis, RaMP enables batch and complex queries (e.g., list all metabolites involved in glycolysis and lung cancer), can readily be integrated into pathway analysis tools, and supports pathway overrepresentation analysis given a list of genes and/or metabolites of interest. For usability, we have developed a RaMP R package (https://github.com/Mathelab/RaMP-DB), including a user-friendly RShiny web application, that supports basic simple and batch queries, pathway overrepresentation analysis given a list of genes or metabolites of interest, and network visualization of gene-metabolite relationships. The package also includes the raw database file (mysql dump), thereby providing a stand-alone downloadable framework for public use and integration with other tools. In addition, the Python code needed to recreate the database on another system is also publicly available (https://github.com/Mathelab/RaMP-BackEnd). Updates for databases in RaMP will be checked multiple times a year and RaMP will be updated accordingly.

Networked gamma radiation detection system for tactical deployment

NASA Astrophysics Data System (ADS)

Mukhopadhyay, Sanjoy; Maurer, Richard; Wolff, Ronald; Smith, Ethan; Guss, Paul; Mitchell, Stephen

2015-08-01

A networked gamma radiation detection system with directional sensitivity and energy spectral data acquisition capability is being developed by the National Security Technologies, LLC, Remote Sensing Laboratory to support the close and intense tactical engagement of law enforcement who carry out counterterrorism missions. In the proposed design, three clusters of 2″ × 4″ × 16″ sodium iodide crystals (4 each) with digiBASE-E (for list mode data collection) would be placed on the passenger side of a minivan. To enhance localization and facilitate rapid identification of isotopes, advanced smart real-time localization and radioisotope identification algorithms like WAVRAD (wavelet-assisted variance reduction for anomaly detection) and NSCRAD (nuisance-rejection spectral comparison ratio anomaly detection) will be incorporated. We will test a collection of algorithms and analysis that centers on the problem of radiation detection with a distributed sensor network. We will study the basic characteristics of a radiation sensor network and focus on the trade-offs between false positive alarm rates, true positive alarm rates, and time to detect multiple radiation sources in a large area. Empirical and simulation analyses of critical system parameters, such as number of sensors, sensor placement, and sensor response functions, will be examined. This networked system will provide an integrated radiation detection architecture and framework with (i) a large nationally recognized search database equivalent that would help generate a common operational picture in a major radiological crisis; (ii) a robust reach back connectivity for search data to be evaluated by home teams; and, finally, (iii) a possibility of integrating search data from multi-agency responders.

Shuttle user analysis (study 2.2): Volume 3. Business Risk And Value of Operations in space (BRAVO). Part 4: Computer programs and data look-up

NASA Technical Reports Server (NTRS)

1974-01-01

Computer program listings as well as graphical and tabulated data needed by the analyst to perform a BRAVO analysis were examined. Graphical aid which can be used to determine the earth coverage of satellites in synchronous equatorial orbits was described. A listing for satellite synthesis computer program as well as a sample printout for the DSCS-11 satellite program and a listing of the symbols used in the program were included. The APL language listing for the payload program cost estimating computer program was given. This language is compatible with many of the time sharing remote terminals computers used in the United States. Data on the intelsat communications network was studied. Costs for telecommunications systems leasing, line of sight microwave relay communications systems, submarine telephone cables, and terrestrial power generation systems were also described.

Multi-petascale highly efficient parallel supercomputer

DOE Office of Scientific and Technical Information (OSTI.GOV)

Asaad, Sameh; Bellofatto, Ralph E.; Blocksome, Michael A.

A Multi-Petascale Highly Efficient Parallel Supercomputer of 100 petaflop-scale includes node architectures based upon System-On-a-Chip technology, where each processing node comprises a single Application Specific Integrated Circuit (ASIC). The ASIC nodes are interconnected by a five dimensional torus network that optimally maximize the throughput of packet communications between nodes and minimize latency. The network implements collective network and a global asynchronous network that provides global barrier and notification functions. Integrated in the node design include a list-based prefetcher. The memory system implements transaction memory, thread level speculation, and multiversioning cache that improves soft error rate at the same time andmore » supports DMA functionality allowing for parallel processing message-passing.« less

Contemporary Network Proteomics and Its Requirements

PubMed Central

Goh, Wilson Wen Bin; Wong, Limsoon; Sng, Judy Chia Ghee

2013-01-01

The integration of networks with genomics (network genomics) is a familiar field. Conventional network analysis takes advantage of the larger coverage and relative stability of gene expression measurements. Network proteomics on the other hand has to develop further on two critical factors: (1) expanded data coverage and consistency, and (2) suitable reference network libraries, and data mining from them. Concerning (1) we discuss several contemporary themes that can improve data quality, which in turn will boost the outcome of downstream network analysis. For (2), we focus on network analysis developments, specifically, the need for context-specific networks and essential considerations for localized network analysis. PMID:24833333

Integrated proteomics identified novel activation of dynein IC2-GR-COX-1 signaling in neurofibromatosis type I (NF1) disease model cells.

PubMed

Hirayama, Mio; Kobayashi, Daiki; Mizuguchi, Souhei; Morikawa, Takashi; Nagayama, Megumi; Midorikawa, Uichi; Wilson, Masayo M; Nambu, Akiko N; Yoshizawa, Akiyasu C; Kawano, Shin; Araki, Norie

2013-05-01

Neurofibromatosis type 1 (NF1) tumor suppressor gene product, neurofibromin, functions in part as a Ras-GAP, and though its loss is implicated in the neuronal abnormality of NF1 patients, its precise cellular function remains unclear. To study the molecular mechanism of NF1 pathogenesis, we prepared NF1 gene knockdown (KD) PC12 cells, as a NF1 disease model, and analyzed their molecular (gene and protein) expression profiles with a unique integrated proteomics approach, comprising iTRAQ, 2D-DIGE, and DNA microarrays, using an integrated protein and gene expression analysis chart (iPEACH). In NF1-KD PC12 cells showing abnormal neuronal differentiation after NGF treatment, of 3198 molecules quantitatively identified and listed in iPEACH, 97 molecules continuously up- or down-regulated over time were extracted. Pathway and network analysis further revealed overrepresentation of calcium signaling and transcriptional regulation by glucocorticoid receptor (GR) in the up-regulated protein set, whereas nerve system development was overrepresented in the down-regulated protein set. The novel up-regulated network we discovered, "dynein IC2-GR-COX-1 signaling," was then examined in NF1-KD cells. Validation studies confirmed that NF1 knockdown induces altered splicing and phosphorylation patterns of dynein IC2 isomers, up-regulation and accumulation of nuclear GR, and increased COX-1 expression in NGF-treated cells. Moreover, the neurite retraction phenotype observed in NF1-KD cells was significantly recovered by knockdown of the dynein IC2-C isoform and COX-1. In addition, dynein IC2 siRNA significantly inhibited nuclear translocation and accumulation of GR and up-regulation of COX-1 expression. These results suggest that dynein IC2 up-regulates GR nuclear translocation and accumulation, and subsequently causes increased COX-1 expression, in this NF1 disease model. Our integrated proteomics strategy, which combines multiple approaches, demonstrates that NF1-related neural abnormalities are, in part, caused by up-regulation of dynein IC2-GR-COX-1 signaling, which may be a novel therapeutic target for NF1.

Inequalities in Global Trade: A Cross-Country Comparison of Trade Network Position, Economic Wealth, Pollution and Mortality

PubMed Central

Prell, Christina; Sun, Laixiang; Feng, Kuishuang; Myroniuk, Tyler W.

2015-01-01

In this paper we investigate how structural patterns of international trade give rise to emissions inequalities across countries, and how such inequality in turn impact countries’ mortality rates. We employ Multi-regional Input-Output analysis to distinguish between sulfur-dioxide (SO2) emissions produced within a country’s boarders (production-based emissions) and emissions triggered by consumption in other countries (consumption-based emissions). We use social network analysis to capture countries’ level of integration within the global trade network. We then apply the Prais-Winsten panel estimation technique to a panel data set across 172 countries over 20 years (1990–2010) to estimate the relationships between countries’ level of integration and SO2 emissions, and the impact of trade integration and SO2 emission on mortality rates. Our findings suggest a positive, (log-) linear relationship between a country’s level of integration and both kinds of emissions. In addition, although more integrated countries are mainly responsible for both forms of emissions, our findings indicate that they also tend to experience lower mortality rates. Our approach offers a unique combination of social network analysis with multiregional input-output analysis, which better operationalizes intuitive concepts about global trade and trade structure. PMID:26642202

Integrative neural networks model for prediction of sediment rating curve parameters for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, M.; Mehltretter, S. L.; Gharabaghi, B.; Rudra, R.

2015-12-01

One of the most uncertain modeling tasks in hydrology is the prediction of ungauged stream sediment load and concentration statistics. This study presents integrated artificial neural networks (ANN) models for prediction of sediment rating curve parameters (rating curve coefficient α and rating curve exponent β) for ungauged basins. The ANN models integrate a comprehensive list of input parameters to improve the accuracy achieved; the input parameters used include: soil, land use, topographic, climatic, and hydrometric data sets. The ANN models were trained on the randomly selected 2/3 of the dataset of 94 gauged streams in Ontario, Canada and validated on the remaining 1/3. The developed models have high correlation coefficients of 0.92 and 0.86 for α and β, respectively. The ANN model for the rating coefficient α is directly proportional to rainfall erosivity factor, soil erodibility factor, and apportionment entropy disorder index, whereas it is inversely proportional to vegetation cover and mean annual snowfall. The ANN model for the rating exponent β is directly proportional to mean annual precipitation, the apportionment entropy disorder index, main channel slope, standard deviation of daily discharge, and inversely proportional to the fraction of basin area covered by wetlands and swamps. Sediment rating curves are essential tools for the calculation of sediment load, concentration-duration curve (CDC), and concentration-duration-frequency (CDF) analysis for more accurate assessment of water quality for ungauged basins.

WebGIVI: a web-based gene enrichment analysis and visualization tool.

PubMed

Sun, Liang; Zhu, Yongnan; Mahmood, A S M Ashique; Tudor, Catalina O; Ren, Jia; Vijay-Shanker, K; Chen, Jian; Schmidt, Carl J

2017-05-04

A major challenge of high throughput transcriptome studies is presenting the data to researchers in an interpretable format. In many cases, the outputs of such studies are gene lists which are then examined for enriched biological concepts. One approach to help the researcher interpret large gene datasets is to associate genes and informative terms (iTerm) that are obtained from the biomedical literature using the eGIFT text-mining system. However, examining large lists of iTerm and gene pairs is a daunting task. We have developed WebGIVI, an interactive web-based visualization tool ( http://raven.anr.udel.edu/webgivi/ ) to explore gene:iTerm pairs. WebGIVI was built via Cytoscape and Data Driven Document JavaScript libraries and can be used to relate genes to iTerms and then visualize gene and iTerm pairs. WebGIVI can accept a gene list that is used to retrieve the gene symbols and corresponding iTerm list. This list can be submitted to visualize the gene iTerm pairs using two distinct methods: a Concept Map or a Cytoscape Network Map. In addition, WebGIVI also supports uploading and visualization of any two-column tab separated data. WebGIVI provides an interactive and integrated network graph of gene and iTerms that allows filtering, sorting, and grouping, which can aid biologists in developing hypothesis based on the input gene lists. In addition, WebGIVI can visualize hundreds of nodes and generate a high-resolution image that is important for most of research publications. The source code can be freely downloaded at https://github.com/sunliang3361/WebGIVI . The WebGIVI tutorial is available at http://raven.anr.udel.edu/webgivi/tutorial.php .

Measuring Long-Term Impact Based on Network Centrality: Unraveling Cinematic Citations

PubMed Central

Spitz, Andreas; Horvát, Emőke-Ágnes

2014-01-01

Traditional measures of success for film, such as box-office revenue and critical acclaim, lack the ability to quantify long-lasting impact and depend on factors that are largely external to the craft itself. With the growing number of films that are being created and large-scale data becoming available through crowd-sourced online platforms, an endogenous measure of success that is not reliant on manual appraisal is of increasing importance. In this article we propose such a ranking method based on a combination of centrality indices. We apply the method to a network that contains several types of citations between more than 40,000 international feature films. From this network we derive a list of milestone films, which can be considered to constitute the foundations of cinema. In a comparison to various existing lists of ‘greatest’ films, such as personal favourite lists, voting lists, lists of individual experts, and lists deduced from expert polls, the selection of milestone films is more diverse in terms of genres, actors, and main creators. Our results shed light on the potential of a systematic quantitative investigation based on cinematic influences in identifying the most inspiring creations in world cinema. In a broader perspective, we introduce a novel research question to large-scale citation analysis, one of the most intriguing topics that have been at the forefront of scientific enquiries for the past fifty years and have led to the development of various network analytic methods. In doing so, we transfer widely studied approaches from citation analysis to the the newly emerging field of quantification efforts in the arts. The specific contribution of this paper consists in modelling the multidimensional cinematic references as a growing multiplex network and in developing a methodology for the identification of central films in this network. PMID:25295877

Integrated network analysis and effective tools in plant systems biology

PubMed Central

Fukushima, Atsushi; Kanaya, Shigehiko; Nishida, Kozo

2014-01-01

One of the ultimate goals in plant systems biology is to elucidate the genotype-phenotype relationship in plant cellular systems. Integrated network analysis that combines omics data with mathematical models has received particular attention. Here we focus on the latest cutting-edge computational advances that facilitate their combination. We highlight (1) network visualization tools, (2) pathway analyses, (3) genome-scale metabolic reconstruction, and (4) the integration of high-throughput experimental data and mathematical models. Multi-omics data that contain the genome, transcriptome, proteome, and metabolome and mathematical models are expected to integrate and expand our knowledge of complex plant metabolisms. PMID:25408696

Exploration of the integration of care for persons with a traumatic brain injury using social network analysis methodology.

PubMed

Lamontagne, Marie-Eve

2013-01-01

Integration is a popular strategy to increase the quality of care within systems of care. However, there is no common language, approach or tool allowing for a valid description, comparison and evaluation of integrated care. Social network analysis could be a viable methodology to provide an objective picture of integrated networks. To illustrate social network analysis use in the context of systems of care for traumatic brain injury. We surveyed members of a network using a validated questionnaire to determine the links between them. We determined the density, centrality, multiplexity, and quality of the links reported. The network was described as moderately dense (0.6), the most prevalent link was knowledge, and four organisation members of a consortium were central to the network. Social network analysis allowed us to create a graphic representation of the network. Social network analysis is a useful methodology to objectively characterise integrated networks.

Case Studies of Ecological Integrative Information Systems: The Luquillo and Sevilleta Information Management Systems

NASA Astrophysics Data System (ADS)

San Gil, Inigo; White, Marshall; Melendez, Eda; Vanderbilt, Kristin

The thirty-year-old United States Long Term Ecological Research Network has developed extensive metadata to document their scientific data. Standard and interoperable metadata is a core component of the data-driven analytical solutions developed by this research network Content management systems offer an affordable solution for rapid deployment of metadata centered information management systems. We developed a customized integrative metadata management system based on the Drupal content management system technology. Building on knowledge and experience with the Sevilleta and Luquillo Long Term Ecological Research sites, we successfully deployed the first two medium-scale customized prototypes. In this paper, we describe the vision behind our Drupal based information management instances, and list the features offered through these Drupal based systems. We also outline the plans to expand the information services offered through these metadata centered management systems. We will conclude with the growing list of participants deploying similar instances.

Integrated Analysis of Dysregulated miRNA-gene Expression in HMGA2-silenced Retinoblastoma Cells

PubMed Central

Venkatesan, Nalini; Deepa, PR; Vasudevan, Madavan; Khetan, Vikas; Reddy, Ashwin M; Krishnakumar, Subramanian

2014-01-01

Retinoblastoma (RB) is a primary childhood eye cancer. HMGA2 shows promise as a molecule for targeted therapy. The involvement of miRNAs in genome-level molecular dys-regulation in HMGA2-silenced RB cells is poorly understood. Through miRNA expression microarray profiling, and an integrated array analysis of the HMGA2-silenced RB cells, the dysregulated miRNAs and the miRNA-target relationships were modelled. Loop network analysis revealed a regulatory association between the transcription factor (SOX5) and the deregulated miRNAs (miR-29a, miR-9*, miR-9-3). Silencing of HMGA2 deregulated the vital oncomirs (miR-7, miR-331, miR-26a, miR-221, miR-17~92 and miR-106b∼25) in RB cells. From this list, the role of the miR-106b∼25 cluster was examined further for its expression in primary RB tumor tissues (n = 20). The regulatory targets of miR-106b∼25 cluster namely p21 (cyclin-dependent kinase inhibitor) and BIM (pro-apoptotic gene) were elevated, and apoptotic cell death was observed, in RB tumor cells treated with the specific antagomirs of the miR-106b∼25 cluster. Thus, suppression of miR-106b∼25 cluster controls RB tumor growth. Taken together, HMGA2 mediated anti-tumor effect present in RB is, in part, mediated through the miR-106b∼25 cluster. PMID:25232279

Bioinformatics-based tools in drug discovery: the cartography from single gene to integrative biological networks.

PubMed

Ramharack, Pritika; Soliman, Mahmoud E S

2018-06-01

Originally developed for the analysis of biological sequences, bioinformatics has advanced into one of the most widely recognized domains in the scientific community. Despite this technological evolution, there is still an urgent need for nontoxic and efficient drugs. The onus now falls on the 'omics domain to meet this need by implementing bioinformatics techniques that will allow for the introduction of pioneering approaches in the rational drug design process. Here, we categorize an updated list of informatics tools and explore the capabilities of integrative bioinformatics in disease control. We believe that our review will serve as a comprehensive guide toward bioinformatics-oriented disease and drug discovery research. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Co-author and keyword networks and their clustering appearance in preventive medicine fields in Korea: analysis of papers in the Journal of Preventive Medicine and Public Health, 1991~2006].

PubMed

Jung, Minsoo; Chung, Dongjun

2008-01-01

This study evaluated knowledge structure and its effect factor by analysis of co-author and keyword networks in Korea's preventive medicine sector. The data was extracted from 873 papers listed in the Journal of Preventive Medicine and Public Health, and was transformed into a co-author and keyword matrix where the existence of a 'link' was judged by impact factors calculated by the weight value of the role and rate of author participation. Research achievement was dependent upon the author's status and networking index, as analyzed by neighborhood degree, multidimensional scaling, correspondence analysis, and multiple regression. Co-author networks developed as randomness network in the center of a few high-productivity researchers. In particular, closeness centrality was more developed than degree centrality. Also, power law distribution was discovered in impact factor and research productivity by college affiliation. In multiple regression, the effect of the author's role was significant in both the impact factor calculated by the participatory rate and the number of listed articles. However, the number of listed articles varied by sex. This study shows that the small world phenomenon exists in co-author and keyword networks in a journal, as in citation networks. However, the differentiation of knowledge structure in the field of preventive medicine was relatively restricted by specialization.

Analysis of DNA Sequences by an Optical ime-Integrating Correlator: Proposal

DTIC Science & Technology

1991-11-01

CURRENT TECHNOLOGY 2 3.0 TIME-INTEGRATING CORRELATOR 2 4.0 REPRESENTATIONS OF THE DNA BASES 8 5.0 DNA ANALYSIS STRATEGY 8 6.0 STRATEGY FOR COARSE...1)-correlation peak formed by the AxB term and (2)-pedestal formed by the A + B terms. 7 Figure 4: Short representations of the DNA bases where each...linear scale. 15 x LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits long pseudorandom

Modeling the interdependent network based on two-mode networks

NASA Astrophysics Data System (ADS)

An, Feng; Gao, Xiangyun; Guan, Jianhe; Huang, Shupei; Liu, Qian

2017-10-01

Among heterogeneous networks, there exist obviously and closely interdependent linkages. Unlike existing research primarily focus on the theoretical research of physical interdependent network model. We propose a two-layer interdependent network model based on two-mode networks to explore the interdependent features in the reality. Specifically, we construct a two-layer interdependent loan network and develop several dependent features indices. The model is verified to enable us to capture the loan dependent features of listed companies based on loan behaviors and shared shareholders. Taking Chinese debit and credit market as case study, the main conclusions are: (1) only few listed companies shoulder the main capital transmission (20% listed companies occupy almost 70% dependent degree). (2) The control of these key listed companies will be more effective of avoiding the spreading of financial risks. (3) Identifying the companies with high betweenness centrality and controlling them could be helpful to monitor the financial risk spreading. (4) The capital transmission channel among Chinese financial listed companies and Chinese non-financial listed companies are relatively strong. However, under greater pressure of demand of capital transmission (70% edges failed), the transmission channel, which constructed by debit and credit behavior, will eventually collapse.

Exploration of the integration of care for persons with a traumatic brain injury using social network analysis methodology

PubMed Central

Lamontagne, Marie-Eve

2013-01-01

Introduction Integration is a popular strategy to increase the quality of care within systems of care. However, there is no common language, approach or tool allowing for a valid description, comparison and evaluation of integrated care. Social network analysis could be a viable methodology to provide an objective picture of integrated networks. Goal of the article To illustrate social network analysis use in the context of systems of care for traumatic brain injury. Method We surveyed members of a network using a validated questionnaire to determine the links between them. We determined the density, centrality, multiplexity, and quality of the links reported. Results The network was described as moderately dense (0.6), the most prevalent link was knowledge, and four organisation members of a consortium were central to the network. Social network analysis allowed us to create a graphic representation of the network. Conclusion Social network analysis is a useful methodology to objectively characterise integrated networks. PMID:24250281

Trauma-Exposed Latina Immigrants’ Networks: A Social Network Analysis Approach

PubMed Central

Hurtado-de-Mendoza, Alejandra; Serrano, Adriana; Gonzales, Felisa A.; Fernandez, Nicole C.; Cabling, Mark; Kaltman, Stacey

2015-01-01

Objective Trauma exposure among Latina immigrants is common. Social support networks can buffer the impact of trauma on mental health. This study characterizes the social networks of trauma-exposed Latina immigrants using a social network analysis perspective. Methods In 2011–2012 a convenience sample (n=28) of Latina immigrants with trauma exposure and presumptive depression or posttraumatic stress disorder was recruited from a community clinic in Washington DC. Participants completed a social network assessment and listed up to ten persons in their network (alters). E-Net was used to describe the aggregate structural, interactional, and functional characteristics of networks and Node-XL was used in a case study to diagram one network. Results Most participants listed children (93%), siblings (82%), and friends (71%) as alters, and most alters lived in the US (69%). Perceived emotional support and positive social interaction were higher compared to tangible, language, information, and financial support. A case study illustrates the use of network visualizations to assess the strengths and weaknesses of social networks. Conclusions Targeted social network interventions to enhance supportive networks among trauma-exposed Latina immigrants are warranted. PMID:28078194

Trauma-Exposed Latina Immigrants' Networks: A Social Network Analysis Approach.

PubMed

Hurtado-de-Mendoza, Alejandra; Serrano, Adriana; Gonzales, Felisa A; Fernandez, Nicole C; Cabling, Mark; Kaltman, Stacey

2016-11-01

Trauma exposure among Latina immigrants is common. Social support networks can buffer the impact of trauma on mental health. This study characterizes the social networks of trauma-exposed Latina immigrants using a social network analysis perspective. In 2011-2012 a convenience sample (n=28) of Latina immigrants with trauma exposure and presumptive depression or posttraumatic stress disorder was recruited from a community clinic in Washington DC. Participants completed a social network assessment and listed up to ten persons in their network (alters). E-Net was used to describe the aggregate structural, interactional, and functional characteristics of networks and Node-XL was used in a case study to diagram one network. Most participants listed children (93%), siblings (82%), and friends (71%) as alters, and most alters lived in the US (69%). Perceived emotional support and positive social interaction were higher compared to tangible, language, information, and financial support. A case study illustrates the use of network visualizations to assess the strengths and weaknesses of social networks. Targeted social network interventions to enhance supportive networks among trauma-exposed Latina immigrants are warranted.

Making Connections: Youth Program Strategies for a Generation of Challenge. Commendable Examples from the Levitan Youth Policy Network. Policy Issues Monograph.

ERIC Educational Resources Information Center

Pines, Marion, Ed.

This document profiles nine youth programs, illustrating concepts, strategies, and lessons available to communities as they start to form an integrated network of essential services designed to prepare out-of-school youth for success in the job market of the 21st century. "Introduction" (Marion Pines) lists considerations when planning a…

Movement of Fuel Ashore: Storage, Capacity, Throughput, and Distribution Analysis

DTIC Science & Technology

2015-12-01

89  ix LIST OF FIGURES Figure 1.  Principles of Operational Maneuver from the Sea ........................... 7  Figure 2.  Compositing and...30  Table 2.  Force Mix Composition ...procedures, and force composition . Such alterations represent an acceptance of operational risk to buy down the foundational risk that the logistics network

Integrating network ecology with applied conservation: a synthesis and guide to implementation.

PubMed

Kaiser-Bunbury, Christopher N; Blüthgen, Nico

2015-07-10

Ecological networks are a useful tool to study the complexity of biotic interactions at a community level. Advances in the understanding of network patterns encourage the application of a network approach in other disciplines than theoretical ecology, such as biodiversity conservation. So far, however, practical applications have been meagre. Here we present a framework for network analysis to be harnessed to advance conservation management by using plant-pollinator networks and islands as model systems. Conservation practitioners require indicators to monitor and assess management effectiveness and validate overall conservation goals. By distinguishing between two network attributes, the 'diversity' and 'distribution' of interactions, on three hierarchical levels (species, guild/group and network) we identify seven quantitative metrics to describe changes in network patterns that have implications for conservation. Diversity metrics are partner diversity, vulnerability/generality, interaction diversity and interaction evenness, and distribution metrics are the specialization indices d' and [Formula: see text] and modularity. Distribution metrics account for sampling bias and may therefore be suitable indicators to detect human-induced changes to plant-pollinator communities, thus indirectly assessing the structural and functional robustness and integrity of ecosystems. We propose an implementation pathway that outlines the stages that are required to successfully embed a network approach in biodiversity conservation. Most importantly, only if conservation action and study design are aligned by practitioners and ecologists through joint experiments, are the findings of a conservation network approach equally beneficial for advancing adaptive management and ecological network theory. We list potential obstacles to the framework, highlight the shortfall in empirical, mostly experimental, network data and discuss possible solutions. Published by Oxford University Press on behalf of the Annals of Botany Company.

Testing can counteract proactive interference by integrating competing information.

PubMed

Wahlheim, Christopher N

2015-01-01

Testing initially learned information before presenting new information has been shown to counteract the deleterious effects of proactive interference by segregating competing sources of information. The present experiments were conducted to demonstrate that testing can also have its effects in part by integrating competing information. Variations of classic A-B, A-D paired-associate learning paradigms were employed that included two lists of word pairs and a cued-recall test. Repeated pairs appeared in both lists (A-B, A-B), control pairs appeared in List 2 only (A-B, C-D), and changed pairs appeared with the same cue in both lists but with different responses (A-B, A-D). The critical manipulation was whether pairs were tested or restudied in an interpolated phase that occurred between Lists 1 and 2. On a final cued-recall test, participants recalled List 2 responses and then indicated when they recollected that responses had earlier changed between lists. The change recollection measure indexed the extent to which competing responses were integrated during List 2. Change was recollected more often for tested than for restudied pairs. Proactive facilitation was obtained in cued recall when change was recollected, whereas proactive interference was obtained when change was not recollected. These results provide evidence that testing counteracted proactive interference in part by making List 1 responses more accessible during List 2, thus promoting integration and increasing later recollection of change. These results have theoretical implications because they show that testing can counteract proactive interference by integrating or segregating competing information.

The list-composition effect in memory for emotional and neutral pictures: Differential contribution of ventral and dorsal attention networks to successful encoding.

PubMed

Barnacle, Gemma E; Montaldi, Daniela; Talmi, Deborah; Sommer, Tobias

2016-09-01

The Emotional enhancement of memory (EEM) is observed in immediate free-recall memory tests when emotional and neutral stimuli are encoded and tested together ("mixed lists"), but surprisingly, not when they are encoded and tested separately ("pure lists"). Here our aim was to investigate whether the effect of list-composition (mixed versus pure lists) on the EEM is due to differential allocation of attention. We scanned participants with fMRI during encoding of semantically-related emotional (negative valence only) and neutral pictures. Analysis of memory performance data replicated previous work, demonstrating an interaction between list composition and emotional valence. In mixed lists, neural subsequent memory effects in the dorsal attention network were greater for neutral stimulus encoding, while neural subsequent memory effects for emotional stimuli were found in a region associated with the ventral attention network. These results imply that when life experiences include both emotional and neutral elements, memory for the latter is more highly correlated with neural activity representing goal-directed attention processing at encoding. Copyright © 2016. Published by Elsevier Ltd.

GIANT 2.0: genome-scale integrated analysis of gene networks in tissues.

PubMed

Wong, Aaron K; Krishnan, Arjun; Troyanskaya, Olga G

2018-05-25

GIANT2 (Genome-wide Integrated Analysis of gene Networks in Tissues) is an interactive web server that enables biomedical researchers to analyze their proteins and pathways of interest and generate hypotheses in the context of genome-scale functional maps of human tissues. The precise actions of genes are frequently dependent on their tissue context, yet direct assay of tissue-specific protein function and interactions remains infeasible in many normal human tissues and cell-types. With GIANT2, researchers can explore predicted tissue-specific functional roles of genes and reveal changes in those roles across tissues, all through interactive multi-network visualizations and analyses. Additionally, the NetWAS approach available through the server uses tissue-specific/cell-type networks predicted by GIANT2 to re-prioritize statistical associations from GWAS studies and identify disease-associated genes. GIANT2 predicts tissue-specific interactions by integrating diverse functional genomics data from now over 61 400 experiments for 283 diverse tissues and cell-types. GIANT2 does not require any registration or installation and is freely available for use at http://giant-v2.princeton.edu.

Knowledge-based compact disease models identify new molecular players contributing to early-stage Alzheimer’s disease

PubMed Central

2013-01-01

Background High-throughput profiling of human tissues typically yield as results the gene lists comprised of a mix of relevant molecular entities with multiple false positives that obstruct the translation of such results into mechanistic hypotheses. From general probabilistic considerations, gene lists distilled for the mechanistically relevant components can be far more useful for subsequent experimental design or data interpretation. Results The input candidate gene lists were processed into different tiers of evidence consistency established by enrichment analysis across subsets of the same experiments and across different experiments and platforms. The cut-offs were established empirically through ontological and semantic enrichment; resultant shortened gene list was re-expanded by Ingenuity Pathway Assistant tool. The resulting sub-networks provided the basis for generating mechanistic hypotheses that were partially validated by literature search. This approach differs from previous consistency-based studies in that the cut-off on the Receiver Operating Characteristic of the true-false separation process is optimized by flexible selection of the consistency building procedure. The gene list distilled by this analytic technique and its network representation were termed Compact Disease Model (CDM). Here we present the CDM signature for the study of early-stage Alzheimer’s disease. The integrated analysis of this gene signature allowed us to identify the protein traffic vesicles as prominent players in the pathogenesis of Alzheimer’s. Considering the distances and complexity of protein trafficking in neurons, it is plausible that spontaneous protein misfolding along with a shortage of growth stimulation result in neurodegeneration. Several potentially overlapping scenarios of early-stage Alzheimer pathogenesis have been discussed, with an emphasis on the protective effects of AT-1 mediated antihypertensive response on cytoskeleton remodeling, along with neuronal activation of oncogenes, luteinizing hormone signaling and insulin-related growth regulation, forming a pleiotropic model of its early stages. Alignment with emerging literature confirmed many predictions derived from early-stage Alzheimer’s disease’ CDM. Conclusions A flexible approach for high-throughput data analysis, the Compact Disease Model generation, allows extraction of meaningful, mechanism-centered gene sets compatible with instant translation of the results into testable hypotheses. PMID:24196233

Towards an integrated EU data system within AtlantOS project

NASA Astrophysics Data System (ADS)

Pouliquen, Sylvie; Harscoat, Valerie; Waldmann, Christoph; Koop-Jakobsen, ketill

2017-04-01

The H2020 AtlantOS project started in June 2015 and aims to optimise and enhance the Integrated Atlantic Ocean Observing Systems (IAOOS). One goal is to ensure that data from different and diverse in-situ observing networks are readily accessible and useable to the wider community, international ocean science community and other stakeholders in this field. To achieve that, the strategy is to move towards an integrated data system within AtlantOS that harmonises work flows, data processing and distribution across the in-situ observing network systems, and integrates in-situ observations in existing European and international data infrastructures (Copernicus marine service, SeaDataNet NODCs, EMODnet, OBIS, GEOSS) so called Integrators. The targeted integrated system will deal with data management challenges for efficient and reliable data service to users: • Quality control commons for heterogeneous and nearly real time data • Standardisation of mandatory metadata for efficient data exchange • Interoperability of network and integrator data management systems Presently the situation is that the data acquired by the different in situ observing networks contributing to the AtlantOS project are processed and distributed using different methodologies and means. Depending on the network data management organization, the data are either processed following recommendations elaborated y the network teams and accessible through a unique portal (FTP or Web), or are processed by individual scientific researchers and made available through National Data Centres or directly at institution level. Some datasets are available through Integrators, such as Copernicus or EMODnet, but connected through ad-hoc links. To facilitate the access to the Atlantic observations and avoid "mixing pears with apples", it has been necessary to agree on (1) the EOVs list and definition across the Networks, (2) a minimum set of common vocabularies for metadata and data description to be used by all the Networks, and (3) a minimum level of Near Real Time Quality Control Procedures for selected EOVs. Then a data exchange backbone has been defined and is being setting up to facilitate discovery, viewing and downloading by the users. Some tools will be recommended to help Network plugging their data on this backbone and facilitate integration in the Integrators. Finally, existing services to the users for data discovery, viewing and downloading will be enhanced to ease access to existing observations. An initial working phase relying on existing international standards and protocols, involving data providers, both Networks and Integrators, and dealing with data harmonisation and integration objectives, has led to agreements and recommendations .The setup phase has started, both on Networks and Integrators sides, to adapt the existing systems in order to move toward this integrated EU data system within AtlantOS as well as collaboration with international partners arpound the ATlantic Ocean.

Analysis of DNA Sequences by an Optical Time-Integrating Correlator: Proposal

DTIC Science & Technology

1991-11-01

OF THE PROBLEM AND CURRENT TECHNOLOGY 2 3.0 TIME-INTEGRATING CORRELATOR 2 4.0 REPRESENTATIONS OF THE DNA BASES 8 5.0 DNA ANALYSIS STRATEGY 8 6.0... DNA bases where each base is represented by a 7-bits long pseudorandom sequence. 9 Figure 5: The flow of data in a DNA analysis system based on an...logarithmic scale and a linear scale. 15 x LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits

Analysis and Design of a Distributed System for Management and Distribution of Natural Language Assertions

DTIC Science & Technology

2010-09-01

5 2. SCIL Architecture ...............................................................................6 3. Assertions...137 x THIS PAGE INTENTIONALLY LEFT BLANK xi LIST OF FIGURES Figure 1. SCIL architecture...Database Connectivity LAN Local Area Network ODBC Open Database Connectivity SCIL Social-Cultural Content in Language UMD

Preliminary Results Obtained in Integrated Safety Analysis of NASA Aviation Safety Program Technologies

NASA Technical Reports Server (NTRS)

2000-01-01

This is a quarterly listing of unclassified AGARD and RTO technical publications NASA received and announced in the NASA STI Database. Contents include 1) Sensor Data Fusion and Integration of the Human Element; 2) Planar Optical Measurement Methods for Gas Turbine Components; 3) RTO Highlights 1998, December 1998.

Molecular Interaction Map of the Mammalian Cell Cycle Control and DNA Repair Systems

PubMed Central

Kohn, Kurt W.

1999-01-01

Eventually to understand the integrated function of the cell cycle regulatory network, we must organize the known interactions in the form of a diagram, map, and/or database. A diagram convention was designed capable of unambiguous representation of networks containing multiprotein complexes, protein modifications, and enzymes that are substrates of other enzymes. To facilitate linkage to a database, each molecular species is symbolically represented only once in each diagram. Molecular species can be located on the map by means of indexed grid coordinates. Each interaction is referenced to an annotation list where pertinent information and references can be found. Parts of the network are grouped into functional subsystems. The map shows how multiprotein complexes could assemble and function at gene promoter sites and at sites of DNA damage. It also portrays the richness of connections between the p53-Mdm2 subsystem and other parts of the network. PMID:10436023

Testing can counteract proactive interference by integrating competing information

PubMed Central

Wahlheim, Christopher N.

2015-01-01

Testing initially learned information before presenting new information has been shown to counteract the deleterious effects of proactive interference by segregating competing sources of information. The present experiments were conducted to demonstrate that testing can also have its effects in part by integrating competing information. Variations of classic A–B, A–D paired-associate learning paradigms were employed that included two lists of word pairs and a cued-recall test. Repeated pairs appeared in both lists (A–B, A–B), control pairs appeared in List 2 only (A–B, C–D), and changed pairs appeared with the same cue in both lists but with different responses (A–B, A–D). The critical manipulation was whether pairs were tested or restudied in an interpolated phase that occurred between Lists 1 and 2. On a final cued-recall test, participants recalled List 2 responses and then indicated when they recollected that responses had earlier changed between lists. The change recollection measure indexed the extent to which competing responses were integrated during List 2. Change was recollected more often for tested than for restudied pairs. Proactive facilitation was obtained in cued recall when change was recollected, whereas proactive interference was obtained when change was not recollected. These results provide evidence that testing counteracted proactive interference in part by making List 1 responses more accessible during List 2, thus promoting integration and increasing later recollection of change. These results have theoretical implications because they show that testing can counteract proactive interference by integrating or segregating competing information. PMID:25120241

Autophagy Regulatory Network - a systems-level bioinformatics resource for studying the mechanism and regulation of autophagy.

PubMed

Türei, Dénes; Földvári-Nagy, László; Fazekas, Dávid; Módos, Dezső; Kubisch, János; Kadlecsik, Tamás; Demeter, Amanda; Lenti, Katalin; Csermely, Péter; Vellai, Tibor; Korcsmáros, Tamás

2015-01-01

Autophagy is a complex cellular process having multiple roles, depending on tissue, physiological, or pathological conditions. Major post-translational regulators of autophagy are well known, however, they have not yet been collected comprehensively. The precise and context-dependent regulation of autophagy necessitates additional regulators, including transcriptional and post-transcriptional components that are listed in various datasets. Prompted by the lack of systems-level autophagy-related information, we manually collected the literature and integrated external resources to gain a high coverage autophagy database. We developed an online resource, Autophagy Regulatory Network (ARN; http://autophagy-regulation.org), to provide an integrated and systems-level database for autophagy research. ARN contains manually curated, imported, and predicted interactions of autophagy components (1,485 proteins with 4,013 interactions) in humans. We listed 413 transcription factors and 386 miRNAs that could regulate autophagy components or their protein regulators. We also connected the above-mentioned autophagy components and regulators with signaling pathways from the SignaLink 2 resource. The user-friendly website of ARN allows researchers without computational background to search, browse, and download the database. The database can be downloaded in SQL, CSV, BioPAX, SBML, PSI-MI, and in a Cytoscape CYS file formats. ARN has the potential to facilitate the experimental validation of novel autophagy components and regulators. In addition, ARN helps the investigation of transcription factors, miRNAs and signaling pathways implicated in the control of the autophagic pathway. The list of such known and predicted regulators could be important in pharmacological attempts against cancer and neurodegenerative diseases.

Investigation on law and economics of listed companies’ financing preference based on complex network theory

PubMed Central

Yang, Jian; Bai, Shuying; Qu, Zhao; Chang, Hui

2017-01-01

In this paper, complex network theory is used to make time-series analysis of key indicators of governance structure and financing data. We analyze scientific listed companies’ governance data from 2010 to 2014 and divide them into groups in accordance with the similarity they share. Then we select sample companies to analyze their financing data and explore the influence of governance structure on financing decision and the financing preference they display. This paper reviews relevant laws and regulations of financing from the perspective of law and economics, then proposes reasonable suggestions to consummate the law for the purpose of regulating listed companies’ financing. The research provides a reference for making qualitative analysis on companies’ financing. PMID:28301510

Investigation on law and economics of listed companies' financing preference based on complex network theory.

PubMed

Yang, Jian; Bai, Shuying; Qu, Zhao; Chang, Hui

2017-01-01

In this paper, complex network theory is used to make time-series analysis of key indicators of governance structure and financing data. We analyze scientific listed companies' governance data from 2010 to 2014 and divide them into groups in accordance with the similarity they share. Then we select sample companies to analyze their financing data and explore the influence of governance structure on financing decision and the financing preference they display. This paper reviews relevant laws and regulations of financing from the perspective of law and economics, then proposes reasonable suggestions to consummate the law for the purpose of regulating listed companies' financing. The research provides a reference for making qualitative analysis on companies' financing.

Integrating data from biological experiments into metabolic networks with the DBE information system.

PubMed

Borisjuk, Ljudmilla; Hajirezaei, Mohammad-Reza; Klukas, Christian; Rolletschek, Hardy; Schreiber, Falk

2005-01-01

Modern 'omics'-technologies result in huge amounts of data about life processes. For analysis and data mining purposes this data has to be considered in the context of the underlying biological networks. This work presents an approach for integrating data from biological experiments into metabolic networks by mapping the data onto network elements and visualising the data enriched networks automatically. This methodology is implemented in DBE, an information system that supports the analysis and visualisation of experimental data in the context of metabolic networks. It consists of five parts: (1) the DBE-Database for consistent data storage, (2) the Excel-Importer application for the data import, (3) the DBE-Website as the interface for the system, (4) the DBE-Pictures application for the up- and download of binary (e. g. image) files, and (5) DBE-Gravisto, a network analysis and graph visualisation system. The usability of this approach is demonstrated in two examples.

BiologicalNetworks 2.0 - an integrative view of genome biology data

PubMed Central

2010-01-01

Background A significant problem in the study of mechanisms of an organism's development is the elucidation of interrelated factors which are making an impact on the different levels of the organism, such as genes, biological molecules, cells, and cell systems. Numerous sources of heterogeneous data which exist for these subsystems are still not integrated sufficiently enough to give researchers a straightforward opportunity to analyze them together in the same frame of study. Systematic application of data integration methods is also hampered by a multitude of such factors as the orthogonal nature of the integrated data and naming problems. Results Here we report on a new version of BiologicalNetworks, a research environment for the integral visualization and analysis of heterogeneous biological data. BiologicalNetworks can be queried for properties of thousands of different types of biological entities (genes/proteins, promoters, COGs, pathways, binding sites, and other) and their relations (interactions, co-expression, co-citations, and other). The system includes the build-pathways infrastructure for molecular interactions/relations and module discovery in high-throughput experiments. Also implemented in BiologicalNetworks are the Integrated Genome Viewer and Comparative Genomics Browser applications, which allow for the search and analysis of gene regulatory regions and their conservation in multiple species in conjunction with molecular pathways/networks, experimental data and functional annotations. Conclusions The new release of BiologicalNetworks together with its back-end database introduces extensive functionality for a more efficient integrated multi-level analysis of microarray, sequence, regulatory, and other data. BiologicalNetworks is freely available at http://www.biologicalnetworks.org. PMID:21190573

Shareholding Networks in Japan

NASA Astrophysics Data System (ADS)

Souma, Wataru; Fujiwara, Yoshi; Aoyama, Hideaki

2005-06-01

The Japanese shareholding network existing at the end of March 2002 is studied empirically. The network is constructed from 2,303 listed companies and 53 non-listed financial institutions. We consider this network as a directed graph by drawing edges from shareholders to stock corporations. The lengths of the shareholder lists vary with the companies, and the most comprehensive lists contain the top 30 shareholders. Consequently, the distribution of incoming edges has an upper bound, while that of outgoing edges has no bound. The distribution of outgoing degrees is well explained by the power law function with an exponential tail. The exponent in the power law range is γ = 1.7. To understand these features from the viewpoint of a company's growth, we consider the correlations between the outgoing degree and the company's age, profit, and total assets.

Integrated network capacity analysis for freight railroads.

DOT National Transportation Integrated Search

2016-02-23

Rail network capacity analysis should consider all network infrastructures in an integrated way, with the challenges of the nonlinear relationships at each network element, a link or a node, and complexity of the interaction between various network e...

Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data.

PubMed

Nabavi, Sheida

2016-08-15

With advances in technologies, huge amounts of multiple types of high-throughput genomics data are available. These data have tremendous potential to identify new and clinically valuable biomarkers to guide the diagnosis, assessment of prognosis, and treatment of complex diseases, such as cancer. Integrating, analyzing, and interpreting big and noisy genomics data to obtain biologically meaningful results, however, remains highly challenging. Mining genomics datasets by utilizing advanced computational methods can help to address these issues. To facilitate the identification of a short list of biologically meaningful genes as candidate drivers of anti-cancer drug resistance from an enormous amount of heterogeneous data, we employed statistical machine-learning techniques and integrated genomics datasets. We developed a computational method that integrates gene expression, somatic mutation, and copy number aberration data of sensitive and resistant tumors. In this method, an integrative method based on module network analysis is applied to identify potential driver genes. This is followed by cross-validation and a comparison of the results of sensitive and resistance groups to obtain the final list of candidate biomarkers. We applied this method to the ovarian cancer data from the cancer genome atlas. The final result contains biologically relevant genes, such as COL11A1, which has been reported as a cis-platinum resistant biomarker for epithelial ovarian carcinoma in several recent studies. The described method yields a short list of aberrant genes that also control the expression of their co-regulated genes. The results suggest that the unbiased data driven computational method can identify biologically relevant candidate biomarkers. It can be utilized in a wide range of applications that compare two conditions with highly heterogeneous datasets.

Research on the relationships of the domestic mutual investment of China based on the cross-shareholding networks of the listed companies

NASA Astrophysics Data System (ADS)

Ma, Yuan-yuan; Zhuang, Xin-tian; Li, Ling-xuan

2011-02-01

Enterprises are the core power and the carriers to promote the country's economy developing sustainably and rapidly; the listed enterprises are the outstanding companies which can represent the economic level at the places where the enterprises are located, so we establish the cross-shareholding networks of the listed companies between 2002 and 2009, and then analyze the mutual investment at company-level, province-level and region-level. We have researched the overall trend of economic development and the overall tendency of capital flow of China in the recent 8 years based on the cross-shareholding networks, the influence of a global economic crisis on the stock markets and the overall economics of China in 2008 and the recovery of the economy after the economic crisis. Moreover, we analyze the variations of the cross-shareholding networks and the influence of the state-owned large and medium enterprises listing frequently on Chinese stock markets. We divide the provinces of China into 3 main categories according to their industrial situations. Though the analysis, we find that the wealth gap between the different areas is not significantly reduced even though the government has carried out strategies such as the Development of the West Regions and the Rejuvenation of Old Industrial Bases in Northeastern China. We analyze the cumulative distribution function of the degree of the vertices and use large amounts of data to do empirical analysis. The methods used include the hierarchical cluster analysis, regression analysis, etc.

IOOC Organizational Network (ION) Project

NASA Astrophysics Data System (ADS)

Dean, H.

2013-12-01

In order to meet the growing need for ocean information, research communities at the national and international levels have responded most recently by developing organizational frameworks that can help to integrate information across systems of existing networks and standardize methods of data gathering, management, and processing that facilitate integration. To address recommendations and identified challenges related to the need for a better understanding of ocean observing networks, members of the U.S. Interagency Ocean Observation Committee (IOOC) supported pursuing a project that came to be titled the IOOC Organizational Network (ION). The ION tool employs network mapping approaches which mirror approaches developed in academic literature aimed at understanding political networks. Researchers gathered data on the list of global ocean observing organizations included in the Framework for Ocean Observing (FOO), developed in 2012 by the international Task Team for an Integrated Framework for Sustained Ocean Observing. At the international scale, researchers reviewed organizational research plans and documents, websites, and formal international agreement documents. At the U.S. national scale, researchers analyzed legislation, formal inter-agency agreements, work plans, charters, and policy documents. Researchers based analysis of relationships among global organizations and national federal organizations on four broad relationship categories: Communications, Data, Infrastructure, and Human Resources. In addition to the four broad relationship categories, researchers also gathered data on relationship instrument types, strength of relationships, and (at the global level) ocean observing variables. Using network visualization software, researchers then developed a series of dynamic webpages. Researchers used the tool to address questions identified by the ocean observing community, including identifying gaps in global relationships and the types of tools used to develop networks at the U.S. national level. As the ION project goes through beta testing and is utilized to address specific questions posed by the ocean observing community, it will become more refined and more closely linked to user needs and interests.

Comfort with Computers in the Library.

ERIC Educational Resources Information Center

Agati, Joseph

2002-01-01

Sets forth a list of do's and don't's when integrating aesthetics, functionality, and technology into college library computer workstation furniture. The article discusses workstation access for both portable computer users and for staff, whose needs involve desktop computers that are possibly networked with printers and other peripherals. (GR)

Improvements to Integrated Tradespace Analysis of Communications Architectures (ITACA) Network Loading Analysis Tool

NASA Technical Reports Server (NTRS)

Lee, Nathaniel; Welch, Bryan W.

2018-01-01

NASA's SCENIC project aims to simplify and reduce the cost of space mission planning by replicating the analysis capabilities of commercially licensed software which are integrated with relevant analysis parameters specific to SCaN assets and SCaN supported user missions. SCENIC differs from current tools that perform similar analyses in that it 1) does not require any licensing fees, 2) will provide an all-in-one package for various analysis capabilities that normally requires add-ons or multiple tools to complete. As part of SCENIC's capabilities, the ITACA network loading analysis tool will be responsible for assessing the loading on a given network architecture and generating a network service schedule. ITACA will allow users to evaluate the quality of service of a given network architecture and determine whether or not the architecture will satisfy the mission's requirements. ITACA is currently under development, and the following improvements were made during the fall of 2017: optimization of runtime, augmentation of network asset pre-service configuration time, augmentation of Brent's method of root finding, augmentation of network asset FOV restrictions, augmentation of mission lifetimes, and the integration of a SCaN link budget calculation tool. The improvements resulted in (a) 25% reduction in runtime, (b) more accurate contact window predictions when compared to STK(Registered Trademark) contact window predictions, and (c) increased fidelity through the use of specific SCaN asset parameters.

Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods

PubMed Central

Li, Xiaofang; Tian, Run; Gao, Hugh; Yan, Feng; Ying, Le; Yang, Yongkang; Yang, Pei

2018-01-01

Cervical cancer is the leading cause of death with gynecological malignancies. We aimed to explore the molecular mechanism of carcinogenesis and biomarkers for cervical cancer by integrated bioinformatic analysis. We employed RNA-sequencing details of 254 cervical squamous cell carcinomas and 3 normal samples from The Cancer Genome Atlas. To explore the distinct pathways, messenger RNA expression was submitted to a Gene Set Enrichment Analysis. Kyoto Encyclopedia of Genes and Genomes and protein–protein interaction network analysis of differentially expressed genes were performed. Then, we conducted pathway enrichment analysis for modules acquired in protein–protein interaction analysis and obtained a list of pathways in every module. After intersecting the results from the 3 approaches, we evaluated the survival rates of both mutual pathways and genes in the pathway, and 5 survival-related genes were obtained. Finally, Cox hazards ratio analysis of these 5 genes was performed. DNA replication pathway (P < .001; 12 genes included) was suggested to have the strongest association with the prognosis of cervical squamous cancer. In total, 5 of the 12 genes, namely, minichromosome maintenance 2, minichromosome maintenance 4, minichromosome maintenance 5, proliferating cell nuclear antigen, and ribonuclease H2 subunit A were significantly correlated with survival. Minichromosome maintenance 5 was shown as an independent prognostic biomarker for patients with cervical cancer. This study identified a distinct pathway (DNA replication). Five genes which may be prognostic biomarkers and minichromosome maintenance 5 were identified as independent prognostic biomarkers for patients with cervical cancer. PMID:29642758

Tools and Models for Integrating Multiple Cellular Networks

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gerstein, Mark

2015-11-06

In this grant, we have systematically investigated the integrated networks, which are responsible for the coordination of activity between metabolic pathways in prokaryotes. We have developed several computational tools to analyze the topology of the integrated networks consisting of metabolic, regulatory, and physical interaction networks. The tools are all open-source, and they are available to download from Github, and can be incorporated in the Knowledgebase. Here, we summarize our work as follow. Understanding the topology of the integrated networks is the first step toward understanding its dynamics and evolution. For Aim 1 of this grant, we have developed a novelmore » algorithm to determine and measure the hierarchical structure of transcriptional regulatory networks [1]. The hierarchy captures the direction of information flow in the network. The algorithm is generally applicable to regulatory networks in prokaryotes, yeast and higher organisms. Integrated datasets are extremely beneficial in understanding the biology of a system in a compact manner due to the conflation of multiple layers of information. Therefore for Aim 2 of this grant, we have developed several tools and carried out analysis for integrating system-wide genomic information. To make use of the structural data, we have developed DynaSIN for protein-protein interactions networks with various dynamical interfaces [2]. We then examined the association between network topology with phenotypic effects such as gene essentiality. In particular, we have organized E. coli and S. cerevisiae transcriptional regulatory networks into hierarchies. We then correlated gene phenotypic effects by tinkering with different layers to elucidate which layers were more tolerant to perturbations [3]. In the context of evolution, we also developed a workflow to guide the comparison between different types of biological networks across various species using the concept of rewiring [4], and Furthermore, we have developed CRIT for correlation analysis in systems biology [5]. For Aim 3, we have further investigated the scaling relationship that the number of Transcription Factors (TFs) in a genome is proportional to the square of the total number of genes. We have extended the analysis from transcription factors to various classes of functional categories, and from individual categories to joint distribution [6]. By introducing a new analytical framework, we have generalized the original toolbox model to take into account of metabolic network with arbitrary network topology [7].« less

Integrating genome-wide association studies and gene expression data highlights dysregulated multiple sclerosis risk pathways.

PubMed

Liu, Guiyou; Zhang, Fang; Jiang, Yongshuai; Hu, Yang; Gong, Zhongying; Liu, Shoufeng; Chen, Xiuju; Jiang, Qinghua; Hao, Junwei

2017-02-01

Much effort has been expended on identifying the genetic determinants of multiple sclerosis (MS). Existing large-scale genome-wide association study (GWAS) datasets provide strong support for using pathway and network-based analysis methods to investigate the mechanisms underlying MS. However, no shared genetic pathways have been identified to date. We hypothesize that shared genetic pathways may indeed exist in different MS-GWAS datasets. Here, we report results from a three-stage analysis of GWAS and expression datasets. In stage 1, we conducted multiple pathway analyses of two MS-GWAS datasets. In stage 2, we performed a candidate pathway analysis of the large-scale MS-GWAS dataset. In stage 3, we performed a pathway analysis using the dysregulated MS gene list from seven human MS case-control expression datasets. In stage 1, we identified 15 shared pathways. In stage 2, we successfully replicated 14 of these 15 significant pathways. In stage 3, we found that dysregulated MS genes were significantly enriched in 10 of 15 MS risk pathways identified in stages 1 and 2. We report shared genetic pathways in different MS-GWAS datasets and highlight some new MS risk pathways. Our findings provide new insights on the genetic determinants of MS.

STARNET 2: a web-based tool for accelerating discovery of gene regulatory networks using microarray co-expression data

PubMed Central

Jupiter, Daniel; Chen, Hailin; VanBuren, Vincent

2009-01-01

Background Although expression microarrays have become a standard tool used by biologists, analysis of data produced by microarray experiments may still present challenges. Comparison of data from different platforms, organisms, and labs may involve complicated data processing, and inferring relationships between genes remains difficult. Results STARNET 2 is a new web-based tool that allows post hoc visual analysis of correlations that are derived from expression microarray data. STARNET 2 facilitates user discovery of putative gene regulatory networks in a variety of species (human, rat, mouse, chicken, zebrafish, Drosophila, C. elegans, S. cerevisiae, Arabidopsis and rice) by graphing networks of genes that are closely co-expressed across a large heterogeneous set of preselected microarray experiments. For each of the represented organisms, raw microarray data were retrieved from NCBI's Gene Expression Omnibus for a selected Affymetrix platform. All pairwise Pearson correlation coefficients were computed for expression profiles measured on each platform, respectively. These precompiled results were stored in a MySQL database, and supplemented by additional data retrieved from NCBI. A web-based tool allows user-specified queries of the database, centered at a gene of interest. The result of a query includes graphs of correlation networks, graphs of known interactions involving genes and gene products that are present in the correlation networks, and initial statistical analyses. Two analyses may be performed in parallel to compare networks, which is facilitated by the new HEATSEEKER module. Conclusion STARNET 2 is a useful tool for developing new hypotheses about regulatory relationships between genes and gene products, and has coverage for 10 species. Interpretation of the correlation networks is supported with a database of previously documented interactions, a test for enrichment of Gene Ontology terms, and heat maps of correlation distances that may be used to compare two networks. The list of genes in a STARNET network may be useful in developing a list of candidate genes to use for the inference of causal networks. The tool is freely available at , and does not require user registration. PMID:19828039

JOURNAL SCOPE GUIDELINES: Paper classification scheme

NASA Astrophysics Data System (ADS)

2005-06-01

This scheme is used to clarify the journal's scope and enable authors and readers to more easily locate the appropriate section for their work. For each of the sections listed in the scope statement we suggest some more detailed subject areas which help define that subject area. These lists are by no means exhaustive and are intended only as a guide to the type of papers we envisage appearing in each section. We acknowledge that no classification scheme can be perfect and that there are some papers which might be placed in more than one section. We are happy to provide further advice on paper classification to authors upon request (please email jphysa@iop.org). 1. Statistical physics numerical and computational methods statistical mechanics, phase transitions and critical phenomena quantum condensed matter theory Bose-Einstein condensation strongly correlated electron systems exactly solvable models in statistical mechanics lattice models, random walks and combinatorics field-theoretical models in statistical mechanics disordered systems, spin glasses and neural networks nonequilibrium systems network theory 2. Chaotic and complex systems nonlinear dynamics and classical chaos fractals and multifractals quantum chaos classical and quantum transport cellular automata granular systems and self-organization pattern formation biophysical models 3. Mathematical physics combinatorics algebraic structures and number theory matrix theory classical and quantum groups, symmetry and representation theory Lie algebras, special functions and orthogonal polynomials ordinary and partial differential equations difference and functional equations integrable systems soliton theory functional analysis and operator theory inverse problems geometry, differential geometry and topology numerical approximation and analysis geometric integration computational methods 4. Quantum mechanics and quantum information theory coherent states eigenvalue problems supersymmetric quantum mechanics scattering theory relativistic quantum mechanics semiclassical approximations foundations of quantum mechanics and measurement theory entanglement and quantum nonlocality geometric phases and quantum tomography quantum tunnelling decoherence and open systems quantum cryptography, communication and computation theoretical quantum optics 5. Classical and quantum field theory quantum field theory gauge and conformal field theory quantum electrodynamics and quantum chromodynamics Casimir effect integrable field theory random matrix theory applications in field theory string theory and its developments classical field theory and electromagnetism metamaterials 6. Fluid and plasma theory turbulence fundamental plasma physics kinetic theory magnetohydrodynamics and multifluid descriptions strongly coupled plasmas one-component plasmas non-neutral plasmas astrophysical and dusty plasmas

Who Are the Most Influential Emergency Physicians on Twitter?

PubMed Central

Riddell, Jeff; Brown, Alisha; Kovic, Ivor; Jauregui, Joshua

2017-01-01

Introduction Twitter has recently gained popularity in emergency medicine (EM). Opinion leaders on Twitter have significant influence on the conversation and content, yet little is known about these opinion leaders. We aimed to describe a methodology to identify the most influential emergency physicians (EP) on Twitter and present a current list. Methods We analyzed 2,234 English-language EPs on Twitter from a previously published list of Twitter accounts generated by a snowball sampling technique. Using NodeXL software, we performed a network analysis of these EPs and ranked them on three measures of influence: in-degree centrality, eigenvector centrality, and betweenness centrality. We analyzed the top 100 users in each of these three measures of influence and compiled a list of users found in the top 100 in all three measures. Results Of the 300 total users identified by one of the measures of influence, there were 142 unique users. Of the 142 unique users, 61 users were in the top 100 on all three measures of influence. We identify these 61 users as the most influential EM Twitter users. Conclusion We both describe a method for identifying the most influential users and provide a list of the 61 most influential EPs on Twitter as of January 1, 2016. This application of network science to the EM Twitter community can guide future research to better understand the networked global community of EM. PMID:28210365

Who Are the Most Influential Emergency Physicians on Twitter?

PubMed

Riddell, Jeff; Brown, Alisha; Kovic, Ivor; Jauregui, Joshua

2017-02-01

Twitter has recently gained popularity in emergency medicine (EM). Opinion leaders on Twitter have significant influence on the conversation and content, yet little is known about these opinion leaders. We aimed to describe a methodology to identify the most influential emergency physicians (EP) on Twitter and present a current list. We analyzed 2,234 English-language EPs on Twitter from a previously published list of Twitter accounts generated by a snowball sampling technique. Using NodeXL software, we performed a network analysis of these EPs and ranked them on three measures of influence: in-degree centrality, eigenvector centrality, and betweenness centrality. We analyzed the top 100 users in each of these three measures of influence and compiled a list of users found in the top 100 in all three measures. Of the 300 total users identified by one of the measures of influence, there were 142 unique users. Of the 142 unique users, 61 users were in the top 100 on all three measures of influence. We identify these 61 users as the most influential EM Twitter users. We both describe a method for identifying the most influential users and provide a list of the 61 most influential EPs on Twitter as of January 1, 2016. This application of network science to the EM Twitter community can guide future research to better understand the networked global community of EM.

Analysis of DNA Sequences by An Optical Time-Integrating Correlator: Proof-Of-Concept Experiments.

DTIC Science & Technology

1992-05-01

TABLES xv LIST OF ABBREVIATIONS xvii 1.0 INTRODUCTION 1 2.0 DNA ANALYSIS STRATEGY 4 2.1 Representation of DNA Bases 4 2.2 DNA Analysis Strategy 6 3.0...Zehnder architecture. 3 Figure 3: Short representations of the DNA bases where each base is represented by a 7-bits long pseudorandom sequence. 5... DNA bases where each base is represented by 7-bits long pseudorandom sequences. 4 Table 2: Long representations of the DNA bases with 255-bits maximum

Computer Science and Technology Publications. NBS Publications List 84.

ERIC Educational Resources Information Center

National Bureau of Standards (DOC), Washington, DC. Inst. for Computer Sciences and Technology.

This bibliography lists publications of the Institute for Computer Sciences and Technology of the National Bureau of Standards. Publications are listed by subject in the areas of computer security, computer networking, and automation technology. Sections list publications of: (1) current Federal Information Processing Standards; (2) computer…

From big data to diagnosis and prognosis: gene expression signatures in liver hepatocellular carcinoma.

PubMed

Yang, Hong; Zhang, Xin; Cai, Xiao-Yong; Wen, Dong-Yue; Ye, Zhi-Hua; Liang, Liang; Zhang, Lu; Wang, Han-Lin; Chen, Gang; Feng, Zhen-Bo

2017-01-01

Liver hepatocellular carcinoma accounts for the overwhelming majority of primary liver cancers and its belated diagnosis and poor prognosis call for novel biomarkers to be discovered, which, in the era of big data, innovative bioinformatics and computational techniques can prove to be highly helpful in. Big data aggregated from The Cancer Genome Atlas and Natural Language Processing were integrated to generate differentially expressed genes. Relevant signaling pathways of differentially expressed genes went through Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes and Panther pathway enrichment analysis and protein-protein interaction network. The pathway ranked high in the enrichment analysis was further investigated, and selected genes with top priority were evaluated and assessed in terms of their diagnostic and prognostic values. A list of 389 genes was generated by overlapping genes from The Cancer Genome Atlas and Natural Language Processing. Three pathways demonstrated top priorities, and the one with specific associations with cancers, 'pathways in cancer,' was analyzed with its four highlighted genes, namely, BIRC5, E2F1, CCNE1, and CDKN2A, which were validated using Oncomine. The detection pool composed of the four genes presented satisfactory diagnostic power with an outstanding integrated AUC of 0.990 (95% CI [0.982-0.998], P  < 0.001, sensitivity: 96.0%, specificity: 96.5%). BIRC5 ( P  = 0.021) and CCNE1 ( P  = 0.027) were associated with poor prognosis, while CDKN2A ( P  = 0.066) and E2F1 ( P  = 0.088) demonstrated no statistically significant differences. The study illustrates liver hepatocellular carcinoma gene signatures, related pathways and networks from the perspective of big data, featuring the cancer-specific pathway with priority, 'pathways in cancer.' The detection pool of the four highlighted genes, namely BIRC5, E2F1, CCNE1 and CDKN2A, should be further investigated given its high evidence level of diagnosis, whereas the prognostic powers of BIRC5 and CCNE1 are equally attractive and worthy of attention.

[SOPHO-NET - a research network on psychotherapy for social phobia].

PubMed

Leichsenring, Falk; Salzer, Simone; Beutel, Manfred E; von Consbruch, Katrin; Herpertz, Stephan; Hiller, Wolfgang; Hoyer, Jürgen; Hüsing, Johannes; Irle, Eva; Joraschky, Peter; Konnopka, Alexander; König, Hans-Helmut; de Liz, Therese; Nolting, Björn; Pöhlmann, Karin; Ruhleder, Mirjana; Schauenburg, Henning; Stangier, Ulrich; Strauss, Bernhard; Subic-Wrana, Claudia; Vormfelde, Stefan V; Weniger, Godehard; Willutzki, Ulrike; Wiltink, Jörg; Leibing, Eric

2009-01-01

This paper presents the Social Phobia Psychotherapy Research Network (SOPHO-NET). SOPHO-NET is among the five research networks on psychotherapy funded by "Bundesministerium für Bildung und Forschung". The research program encompasses a coordinated group of studies of social phobia. In the central project (Study A), a multi-center randomized controlled trial, refined models of manualized cognitive-behavioral therapy (CBT) and manualized short-term psychodynamic psychotherapy (STPP) are compared in the treatment of social phobia. A sample of n=512 outpatients will be randomized to either CBT, STPP or wait list. For quality assurance and treatment integrity, a specific project has been established (Project Q). Study A is complemented by four interrelated projects focusing on attachment style (Study B1), cost-effectiveness (Study B2), polymorphisms in the serotonin transporter gene (Study C1) and on structural and functional deviations of hippocampus and amygdala (Study C2). Thus, the SOPHO-NET program allows for a highly interdisciplinary research of psychotherapy in social phobia.

XLinkDB 2.0: integrated, large-scale structural analysis of protein crosslinking data

PubMed Central

Schweppe, Devin K.; Zheng, Chunxiang; Chavez, Juan D.; Navare, Arti T.; Wu, Xia; Eng, Jimmy K.; Bruce, James E.

2016-01-01

Motivation: Large-scale chemical cross-linking with mass spectrometry (XL-MS) analyses are quickly becoming a powerful means for high-throughput determination of protein structural information and protein–protein interactions. Recent studies have garnered thousands of cross-linked interactions, yet the field lacks an effective tool to compile experimental data or access the network and structural knowledge for these large scale analyses. We present XLinkDB 2.0 which integrates tools for network analysis, Protein Databank queries, modeling of predicted protein structures and modeling of docked protein structures. The novel, integrated approach of XLinkDB 2.0 enables the holistic analysis of XL-MS protein interaction data without limitation to the cross-linker or analytical system used for the analysis. Availability and Implementation: XLinkDB 2.0 can be found here, including documentation and help: http://xlinkdb.gs.washington.edu/. Contact: jimbruce@uw.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153666

ITEP: an integrated toolkit for exploration of microbial pan-genomes.

PubMed

Benedict, Matthew N; Henriksen, James R; Metcalf, William W; Whitaker, Rachel J; Price, Nathan D

2014-01-03

Comparative genomics is a powerful approach for studying variation in physiological traits as well as the evolution and ecology of microorganisms. Recent technological advances have enabled sequencing large numbers of related genomes in a single project, requiring computational tools for their integrated analysis. In particular, accurate annotations and identification of gene presence and absence are critical for understanding and modeling the cellular physiology of newly sequenced genomes. Although many tools are available to compare the gene contents of related genomes, new tools are necessary to enable close examination and curation of protein families from large numbers of closely related organisms, to integrate curation with the analysis of gain and loss, and to generate metabolic networks linking the annotations to observed phenotypes. We have developed ITEP, an Integrated Toolkit for Exploration of microbial Pan-genomes, to curate protein families, compute similarities to externally-defined domains, analyze gene gain and loss, and generate draft metabolic networks from one or more curated reference network reconstructions in groups of related microbial species among which the combination of core and variable genes constitute the their "pan-genomes". The ITEP toolkit consists of: (1) a series of modular command-line scripts for identification, comparison, curation, and analysis of protein families and their distribution across many genomes; (2) a set of Python libraries for programmatic access to the same data; and (3) pre-packaged scripts to perform common analysis workflows on a collection of genomes. ITEP's capabilities include de novo protein family prediction, ortholog detection, analysis of functional domains, identification of core and variable genes and gene regions, sequence alignments and tree generation, annotation curation, and the integration of cross-genome analysis and metabolic networks for study of metabolic network evolution. ITEP is a powerful, flexible toolkit for generation and curation of protein families. ITEP's modular design allows for straightforward extension as analysis methods and tools evolve. By integrating comparative genomics with the development of draft metabolic networks, ITEP harnesses the power of comparative genomics to build confidence in links between genotype and phenotype and helps disambiguate gene annotations when they are evaluated in both evolutionary and metabolic network contexts.

Grey-matter network disintegration as predictor of cognitive and motor function with aging.

PubMed

Koini, Marisa; Duering, Marco; Gesierich, Benno G; Rombouts, Serge A R B; Ropele, Stefan; Wagner, Fabian; Enzinger, Christian; Schmidt, Reinhold

2018-06-01

Loss of grey-matter volume with advancing age affects the entire cortex. It has been suggested that atrophy occurs in a network-dependent manner with advancing age rather than in independent brain areas. The relationship between networks of structural covariance (SCN) disintegration and cognitive functioning during normal aging is not fully explored. We, therefore, aimed to (1) identify networks that lose GM integrity with advancing age, (2) investigate if age-related impairment of integrity in GM networks associates with cognitive function and decreasing fine motor skills (FMS), and (3) examine if GM disintegration is a mediator between age and cognition and FMS. T1-weighted scans of n = 257 participants (age range: 20-87) were used to identify GM networks using independent component analysis. Random forest analysis was implemented to examine the importance of network integrity as predictors of memory, executive functions, and FMS. The associations between GM disintegration, age and cognitive performance, and FMS were assessed using mediation analyses. Advancing age was associated with decreasing cognitive performance and FMS. Fourteen of 20 GM networks showed integrity changes with advancing age. Next to age and education, eight networks (fronto-parietal, fronto-occipital, temporal, limbic, secondary somatosensory, cuneal, sensorimotor network, and a cerebellar network) showed an association with cognition and FMS (up to 15.08%). GM networks partially mediated the effect between age and cognition and age and FMS. We confirm an age-related decline in cognitive functioning and FMS in non-demented community-dwelling subjects and showed that aging selectively affects the integrity of GM networks. The negative effect of age on cognition and FMS is associated with distinct GM networks and is partly mediated by their disintegration.

Analysis of Flow Behavior Within An Integrated Computer-Communication Network,

DTIC Science & Technology

1979-05-01

Howard. Plan today for tomorrows data/voice nets. Data Communications 7, 9 (Sep. 1978), 51-62. 24. F-ark, Howard, and Gitman , Israel. Inteqrated DoD...computer networks. NTC-74, San Diego, CA., (Dec. 2-4, 1974), 1032-1037. 31. Gitman , I., Frank, H., Occhiogrosso, B., and Hsieh, W. Issues in integrated...switched networks agree on standard interface. Data Communications, (May/June 1978), 25)-39. 36. Hsieh, W., Gitman , I., and Occhiogrosso, B. Design of

A Framework for Achieving Situational Awareness during Crisis based on Twitter Analysis

NASA Astrophysics Data System (ADS)

Zielinski, Andrea; Tokarchuk, Laurissa; Middleton, Stuart; Chaves, Fernando

2013-04-01

Decision Support Systems for Natural Crisis Management increasingly employ Web 2.0 and 3.0 technologies for future collaborative decision making, including the use of social networks like Twitter. However, human sensor data is not readily accessible and interpretable, since the texts are unstructured, noisy and available in various languages. The present work focusses on the detection of crisis events in a multilingual setting as part of the FP7-funded EU project TRIDEC and is motivated by the goal to establish a Tsunami warning system for the Mediterranean. It is integrated into a dynamic spatial-temporal decision making component with a command and control unit's graphical user interface that presents all relevant information to the human operator to support critical decision-support. To this end, a tool for the interactive visualization of geospatial data is implemented: All tweets with an exact timestamp or geo-location are monitored on the map in real-time so that the operator on duty can get an overall picture of the situation. Apart from the human sensor data, the seismic sensor data will appear also on the same screen. Signs of abnormal activity from twitter usage in social networks as well as in sensor networks devices can then be used to trigger official warning alerts according to the CAP message standard. Whenever a certain threshold of relevant tweets in a HASC region (Hierarchical Administrative Subdivision Code) is exceeded, the twitter activity in this administrative region will be shown on a map. We believe that the following functionalities are crucial for monitoring crisis, making use of text mining and network analysis techniques: Focussed crawling, trustworthyness analysis geo-parsing, and multilingual tweet classification. In the first step, the Twitter Streaming API accesses the social data, using an adaptive keyword list (focussed crawling). Then, tweets are filtered and aggregated to form counts for a certain time-span (e.g., an interval of 1-2 minutes). Particularly, we investigate the following novel techniques that help to fulfill this task: trustworthyness analysis (linkage analysis and user network analysis), geo-parsing (locating the event in space), and multilingual tweet classification (filtering out of noisy tweets for various Mediterranean languages). Lastly, an aberration algorithm looks for spikes in the temporal stream of twitter data.

Preliminary Results Obtained in Integrated Safety Analysis of NASA Aviation Safety Program Technologies

NASA Technical Reports Server (NTRS)

2005-01-01

This is a listing of recent unclassified RTO technical publications for January 1, 2005 through March 31, 2005 processed by the NASA Center for AeroSpace Center available on the NASA Aeronautics and Space Database. Contents include 1) Electronic Information Management; 2) Decision Support to Combined Joint Task Force and Component Commanders; 3) RTO Technical Publications : A Quarterly Listing (December 2004); 4) The Role of Humans in Intelligent and Automated Systems.

Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation

PubMed Central

Li, Wenyuan; Liu, Chun-Chi; Zhang, Tong; Li, Haifeng; Waterman, Michael S.; Zhou, Xianghong Jasmine

2011-01-01

The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks. PMID:21698123

Design of on-board Bluetooth wireless network system based on fault-tolerant technology

NASA Astrophysics Data System (ADS)

You, Zheng; Zhang, Xiangqi; Yu, Shijie; Tian, Hexiang

2007-11-01

In this paper, the Bluetooth wireless data transmission technology is applied in on-board computer system, to realize wireless data transmission between peripherals of the micro-satellite integrating electronic system, and in view of the high demand of reliability of a micro-satellite, a design of Bluetooth wireless network based on fault-tolerant technology is introduced. The reliability of two fault-tolerant systems is estimated firstly using Markov model, then the structural design of this fault-tolerant system is introduced; several protocols are established to make the system operate correctly, some related problems are listed and analyzed, with emphasis on Fault Auto-diagnosis System, Active-standby switch design and Data-Integrity process.

Optimization of a large-scale microseismic monitoring network in northern Switzerland

NASA Astrophysics Data System (ADS)

Kraft, Toni; Mignan, Arnaud; Giardini, Domenico

2013-10-01

We have developed a network optimization method for regional-scale microseismic monitoring networks and applied it to optimize the densification of the existing seismic network in northeastern Switzerland. The new network will build the backbone of a 10-yr study on the neotectonic activity of this area that will help to better constrain the seismic hazard imposed on nuclear power plants and waste repository sites. This task defined the requirements regarding location precision (0.5 km in epicentre and 2 km in source depth) and detection capability [magnitude of completeness Mc = 1.0 (ML)]. The goal of the optimization was to find the geometry and size of the network that met these requirements. Existing stations in Switzerland, Germany and Austria were considered in the optimization procedure. We based the optimization on the simulated annealing approach proposed by Hardt & Scherbaum, which aims to minimize the volume of the error ellipsoid of the linearized earthquake location problem (D-criterion). We have extended their algorithm to: calculate traveltimes of seismic body waves using a finite difference ray tracer and the 3-D velocity model of Switzerland, calculate seismic body-wave amplitudes at arbitrary stations assuming the Brune source model and using scaling and attenuation relations recently derived for Switzerland, and estimate the noise level at arbitrary locations within Switzerland using a first-order ambient seismic noise model based on 14 land-use classes defined by the EU-project CORINE and open GIS data. We calculated optimized geometries for networks with 10-35 added stations and tested the stability of the optimization result by repeated runs with changing initial conditions. Further, we estimated the attainable magnitude of completeness (Mc) for the different sized optimal networks using the Bayesian Magnitude of Completeness (BMC) method introduced by Mignan et al. The algorithm developed in this study is also applicable to smaller optimization problems, for example, small local monitoring networks. Possible applications are volcano monitoring, the surveillance of induced seismicity associated with geotechnical operations and many more. Our algorithm is especially useful to optimize networks in populated areas with heterogeneous noise conditions and if complex velocity structures or existing stations have to be considered.

GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

PubMed

Zaag, Rim; Tamby, Jean Philippe; Guichard, Cécile; Tariq, Zakia; Rigaill, Guillem; Delannoy, Etienne; Renou, Jean-Pierre; Balzergue, Sandrine; Mary-Huard, Tristan; Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Brunaud, Véronique

2015-01-01

CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein-protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

MONGKIE: an integrated tool for network analysis and visualization for multi-omics data.

PubMed

Jang, Yeongjun; Yu, Namhee; Seo, Jihae; Kim, Sun; Lee, Sanghyuk

2016-03-18

Network-based integrative analysis is a powerful technique for extracting biological insights from multilayered omics data such as somatic mutations, copy number variations, and gene expression data. However, integrated analysis of multi-omics data is quite complicated and can hardly be done in an automated way. Thus, a powerful interactive visual mining tool supporting diverse analysis algorithms for identification of driver genes and regulatory modules is much needed. Here, we present a software platform that integrates network visualization with omics data analysis tools seamlessly. The visualization unit supports various options for displaying multi-omics data as well as unique network models for describing sophisticated biological networks such as complex biomolecular reactions. In addition, we implemented diverse in-house algorithms for network analysis including network clustering and over-representation analysis. Novel functions include facile definition and optimized visualization of subgroups, comparison of a series of data sets in an identical network by data-to-visual mapping and subsequent overlaying function, and management of custom interaction networks. Utility of MONGKIE for network-based visual data mining of multi-omics data was demonstrated by analysis of the TCGA glioblastoma data. MONGKIE was developed in Java based on the NetBeans plugin architecture, thus being OS-independent with intrinsic support of module extension by third-party developers. We believe that MONGKIE would be a valuable addition to network analysis software by supporting many unique features and visualization options, especially for analysing multi-omics data sets in cancer and other diseases. .

Integrated Application of Active Controls (IAAC) technology to an advanced subsonic transport project. ACT/Control/Guidance System study. Volume 2: Appendices

NASA Technical Reports Server (NTRS)

1982-01-01

The integrated application of active controls (IAAC) technology to an advanced subsonic transport is reported. Supplementary technical data on the following topics are included: (1) 1990's avionics technology assessment; (2) function criticality assessment; (3) flight deck system for total control and functional features list; (4) criticality and reliability assessment of units; (5) crew procedural function task analysis; and (6) recommendations for simulation mechanization.

NASCOM network: Ground communications reliability report

NASA Technical Reports Server (NTRS)

1973-01-01

A reliability performance analysis of the NASCOM Network circuits is reported. Network performance narrative summary is presented to include significant changes in circuit configurations, current figures, and trends in each trouble category with notable circuit totals specified. Lost time and interruption tables listing circuits which were affected by outages showing their totals category are submitted. A special analysis of circuits with low reliabilities is developed with tables depicting the performance and graphs for individual reliabilities.

Workflow-Oriented Cyberinfrastructure for Sensor Data Analytics

NASA Astrophysics Data System (ADS)

Orcutt, J. A.; Rajasekar, A.; Moore, R. W.; Vernon, F.

2015-12-01

Sensor streams comprise an increasingly large part of Earth Science data. Analytics based on sensor data require an easy way to perform operations such as acquisition, conversion to physical units, metadata linking, sensor fusion, analysis and visualization on distributed sensor streams. Furthermore, embedding real-time sensor data into scientific workflows is of growing interest. We have implemented a scalable networked architecture that can be used to dynamically access packets of data in a stream from multiple sensors, and perform synthesis and analysis across a distributed network. Our system is based on the integrated Rule Oriented Data System (irods.org), which accesses sensor data from the Antelope Real Time Data System (brtt.com), and provides virtualized access to collections of data streams. We integrate real-time data streaming from different sources, collected for different purposes, on different time and spatial scales, and sensed by different methods. iRODS, noted for its policy-oriented data management, brings to sensor processing features and facilities such as single sign-on, third party access control lists ( ACLs), location transparency, logical resource naming, and server-side modeling capabilities while reducing the burden on sensor network operators. Rich integrated metadata support also makes it straightforward to discover data streams of interest and maintain data provenance. The workflow support in iRODS readily integrates sensor processing into any analytical pipeline. The system is developed as part of the NSF-funded Datanet Federation Consortium (datafed.org). APIs for selecting, opening, reaping and closing sensor streams are provided, along with other helper functions to associate metadata and convert sensor packets into NetCDF and JSON formats. Near real-time sensor data including seismic sensors, environmental sensors, LIDAR and video streams are available through this interface. A system for archiving sensor data and metadata in NetCDF format has been implemented and will be demonstrated at AGU.

Models for Threat Assessment in Networks

DTIC Science & Technology

2006-09-01

Software International and Command AntiVirus . [Online]. Available: http://www.commandsoftware.com/virus/newlove.html [38] C. Ng and P. Ferrie. (2000...28 2.3 False positive trends across all population sizes for r=0.7 and m=0.1 . . . . 33 2.4 False negative trends across all population...benefits analysis is often performed to determine the list of mitigation procedures. Traditionally, risk assessment has been done in part with software

Integrative topological analysis of mass spectrometry data reveals molecular features with clinical relevance in esophageal squamous cell carcinoma

PubMed Central

Gao, She-Gan; Liu, Rui-Min; Zhao, Yun-Gang; Wang, Pei; Ward, Douglas G.; Wang, Guang-Chao; Guo, Xiang-Qian; Gu, Juan; Niu, Wan-Bin; Zhang, Tian; Martin, Ashley; Guo, Zhi-Peng; Feng, Xiao-Shan; Qi, Yi-Jun; Ma, Yuan-Fang

2016-01-01

Combining MS-based proteomic data with network and topological features of such network would identify more clinically relevant molecules and meaningfully expand the repertoire of proteins derived from MS analysis. The integrative topological indexes representing 95.96% information of seven individual topological measures of node proteins were calculated within a protein-protein interaction (PPI) network, built using 244 differentially expressed proteins (DEPs) identified by iTRAQ 2D-LC-MS/MS. Compared with DEPs, differentially expressed genes (DEGs) and comprehensive features (CFs), structurally dominant nodes (SDNs) based on integrative topological index distribution produced comparable classification performance in three different clinical settings using five independent gene expression data sets. The signature molecules of SDN-based classifier for distinction of early from late clinical TNM stages were enriched in biological traits of protein synthesis, intracellular localization and ribosome biogenesis, which suggests that ribosome biogenesis represents a promising therapeutic target for treating ESCC. In addition, ITGB1 expression selected exclusively by integrative topological measures correlated with clinical stages and prognosis, which was further validated with two independent cohorts of ESCC samples. Thus the integrative topological analysis of PPI networks proposed in this study provides an alternative approach to identify potential biomarkers and therapeutic targets from MS/MS data with functional insights in ESCC. PMID:26898710

Community Landscapes: An Integrative Approach to Determine Overlapping Network Module Hierarchy, Identify Key Nodes and Predict Network Dynamics

PubMed Central

Kovács, István A.; Palotai, Robin; Szalay, Máté S.; Csermely, Peter

2010-01-01

Background Network communities help the functional organization and evolution of complex networks. However, the development of a method, which is both fast and accurate, provides modular overlaps and partitions of a heterogeneous network, has proven to be rather difficult. Methodology/Principal Findings Here we introduce the novel concept of ModuLand, an integrative method family determining overlapping network modules as hills of an influence function-based, centrality-type community landscape, and including several widely used modularization methods as special cases. As various adaptations of the method family, we developed several algorithms, which provide an efficient analysis of weighted and directed networks, and (1) determine pervasively overlapping modules with high resolution; (2) uncover a detailed hierarchical network structure allowing an efficient, zoom-in analysis of large networks; (3) allow the determination of key network nodes and (4) help to predict network dynamics. Conclusions/Significance The concept opens a wide range of possibilities to develop new approaches and applications including network routing, classification, comparison and prediction. PMID:20824084

Automated selection of computed tomography display parameters using neural networks

NASA Astrophysics Data System (ADS)

Zhang, Di; Neu, Scott; Valentino, Daniel J.

2001-07-01

A collection of artificial neural networks (ANN's) was trained to identify simple anatomical structures in a set of x-ray computed tomography (CT) images. These neural networks learned to associate a point in an image with the anatomical structure containing the point by using the image pixels located on the horizontal and vertical lines that ran through the point. The neural networks were integrated into a computer software tool whose function is to select an index into a list of CT window/level values from the location of the user's mouse cursor. Based upon the anatomical structure selected by the user, the software tool automatically adjusts the image display to optimally view the structure.

Blacklist Ecosystem Analysis Update: 2014

DTIC Science & Technology

2014-12-01

example, we checked to see if any of the blacklisted IP addresses were known sinkhole IP addresses. This information would essentially invalidate the...indicator as an indicator of malicious activity, since sinkholes are operated by CERTCC-2014-82 4 Blacklist Ecosystem Analysis CERT/CC network defenders who...clean up and collect intelligence on threats. Only one list out of 67, LI_3, contained any sinkhole IP addresses and that list contained only 10. All

Analysis of DNA Sequences by an Optical Time-Integrating Correlator: Proof-of-Concept Experiments.

DTIC Science & Technology

1992-05-01

DNA ANALYSIS STRATEGY 4 2.1 Representation of DNA Bases 4 2.2 DNA Analysis Strategy 6 3.0 CUSTOM GENERATORS FOR DNA SEQUENCES 10 3.1 Hardware Design 10...of the DNA bases where each base is represented by a 7-bits long pseudorandom sequence. 5 Figure 4: Coarse analysis of a DNA sequence. 7 Figure 5: Fine...a 20-bases long database. 32 xiii LIST OF TABLES PAGE Table 1: Short representations of the DNA bases where each base is represented by 7-bits long

Semantic web for integrated network analysis in biomedicine.

PubMed

Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

2009-03-01

The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

Zoos through the Lens of the IUCN Red List: A Global Metapopulation Approach to Support Conservation Breeding Programs

PubMed Central

Conde, Dalia A.; Colchero, Fernando; Gusset, Markus; Pearce-Kelly, Paul; Byers, Onnie; Flesness, Nate; Browne, Robert K.; Jones, Owen R.

2013-01-01

Given current extinction trends, the number of species requiring conservation breeding programs (CBPs) is likely to increase dramatically. To inform CBP policies for threatened terrestrial vertebrates, we evaluated the number and representation of threatened vertebrate species on the IUCN Red List held in the ISIS zoo network and estimated the complexity of their management as metapopulations. Our results show that 695 of the 3,955 (23%) terrestrial vertebrate species in ISIS zoos are threatened. Only two of the 59 taxonomic orders show a higher proportion of threatened species in ISIS zoos than would be expected if species were selected at random. In addition, for most taxa, the management of a zoo metapopulation of more than 250 individuals will require the coordination of a cluster of 11 to 24 ISIS zoos within a radius of 2,000 km. Thus, in the zoo network, the representation of species that may require CBPs is currently low and the spatial distribution of these zoo populations makes management difficult. Although the zoo community may have the will and the logistical potential to contribute to conservation actions, including CBPs, to do so will require greater collaboration between zoos and other institutions, alongside the development of international agreements that facilitate cross-border movement of zoo animals. To maximize the effectiveness of integrated conservation actions that include CBPs, it is fundamental that the non-zoo conservation community acknowledges and integrates the expertise and facilities of zoos where it can be helpful. PMID:24348999

Zoos through the lens of the IUCN Red List: a global metapopulation approach to support conservation breeding programs.

PubMed

Conde, Dalia A; Colchero, Fernando; Gusset, Markus; Pearce-Kelly, Paul; Byers, Onnie; Flesness, Nate; Browne, Robert K; Jones, Owen R

2013-01-01

Given current extinction trends, the number of species requiring conservation breeding programs (CBPs) is likely to increase dramatically. To inform CBP policies for threatened terrestrial vertebrates, we evaluated the number and representation of threatened vertebrate species on the IUCN Red List held in the ISIS zoo network and estimated the complexity of their management as metapopulations. Our results show that 695 of the 3,955 (23%) terrestrial vertebrate species in ISIS zoos are threatened. Only two of the 59 taxonomic orders show a higher proportion of threatened species in ISIS zoos than would be expected if species were selected at random. In addition, for most taxa, the management of a zoo metapopulation of more than 250 individuals will require the coordination of a cluster of 11 to 24 ISIS zoos within a radius of 2,000 km. Thus, in the zoo network, the representation of species that may require CBPs is currently low and the spatial distribution of these zoo populations makes management difficult. Although the zoo community may have the will and the logistical potential to contribute to conservation actions, including CBPs, to do so will require greater collaboration between zoos and other institutions, alongside the development of international agreements that facilitate cross-border movement of zoo animals. To maximize the effectiveness of integrated conservation actions that include CBPs, it is fundamental that the non-zoo conservation community acknowledges and integrates the expertise and facilities of zoos where it can be helpful.

Contextual Hub Analysis Tool (CHAT): A Cytoscape app for identifying contextually relevant hubs in biological networks.

PubMed

Muetze, Tanja; Goenawan, Ivan H; Wiencko, Heather L; Bernal-Llinares, Manuel; Bryan, Kenneth; Lynn, David J

2016-01-01

Highly connected nodes (hubs) in biological networks are topologically important to the structure of the network and have also been shown to be preferentially associated with a range of phenotypes of interest. The relative importance of a hub node, however, can change depending on the biological context. Here, we report a Cytoscape app, the Contextual Hub Analysis Tool (CHAT), which enables users to easily construct and visualize a network of interactions from a gene or protein list of interest, integrate contextual information, such as gene expression or mass spectrometry data, and identify hub nodes that are more highly connected to contextual nodes (e.g. genes or proteins that are differentially expressed) than expected by chance. In a case study, we use CHAT to construct a network of genes that are differentially expressed in Dengue fever, a viral infection. CHAT was used to identify and compare contextual and degree-based hubs in this network. The top 20 degree-based hubs were enriched in pathways related to the cell cycle and cancer, which is likely due to the fact that proteins involved in these processes tend to be highly connected in general. In comparison, the top 20 contextual hubs were enriched in pathways commonly observed in a viral infection including pathways related to the immune response to viral infection. This analysis shows that such contextual hubs are considerably more biologically relevant than degree-based hubs and that analyses which rely on the identification of hubs solely based on their connectivity may be biased towards nodes that are highly connected in general rather than in the specific context of interest. CHAT is available for Cytoscape 3.0+ and can be installed via the Cytoscape App Store ( http://apps.cytoscape.org/apps/chat).

Adaptive Topological Configuration of an Integrated Circuit/Packet-Switched Computer Network.

DTIC Science & Technology

1984-01-01

Gitman et al. [45] state that there are basically two approaches to the integrated network design problem: (1) solve the link/capacity problem for...1972), 1385-1397. 33. Frank, H., and Gitman , I. Economic analysis of integrated voice and data networks: a case study. Proc. of IEEE 66 , 11 (Nov. 1978...1974), 1074-1079. 45. Gitman , I., Hsieh, W., and Occhiogrosso, B. J. Analysis and design of hybrid switching networks. IEEE Trans. on Comm. Com-29

Network meta-analyses performed by contracting companies and commissioned by industry.

PubMed

Schuit, Ewoud; Ioannidis, John Pa

2016-11-25

Industry commissions contracting companies to perform network meta-analysis for health technology assessment (HTA) and reimbursement submissions. Our objective was to estimate the number of network meta-analyses performed by consulting companies contracted by industry, to assess whether they were published, and to explore reasons for non-publication. We searched MEDLINE for network meta-analyses of randomized trials. Papers were included if they had authors affiliated with any contracting company. All identified contracting companies as well as additional ones from the list of the exhibitors at the International Society for Pharmacoeconomics and Outcomes Research, an annual meeting that representatives from many contracting companies attend and exhibit at, were surveyed regarding conduct and publication of network meta-analyses. In 162 of 822 (20%) network meta-analysis papers, authors were affiliated to 66 contracting companies. Another 36 contracting companies were identified by the exhibitors list. Three companies had no contact information and six merged with others, therefore 93 companies were contacted. Thirty seven out of ninety three (40%) companies responded, and 19 indicated that they had performed a total of 476 network meta-analyses, but only 102 (21%) papers were published. Thirteen companies that disclosed to have conducted 174 network meta-analyses (45 published) provided reasons for non-publication. Of the 129 still unpublished meta-analyses, for 40 there were plans for future publication, for 37 the sponsor did not allow publication, for 16 the contracting companies did not plan to publish the meta-analysis, for another 23 plans were unclear, and the remaining 13 were used as HTA submission. The protocol of the network meta-analysis was publically available from 11/162 (6.8%) network meta-analyses published by authors affiliated with contracting companies. There is a prolific sector of professional contracting companies that perform network meta-analyses. Industry commissions many network meta-analyses, but most are not registered before or published after analyses in the scientific literature. Mechanisms to improve publication rates of network meta-analysis commissioned by industry are warranted.

Unified Approach to Modeling and Simulation of Space Communication Networks and Systems

NASA Technical Reports Server (NTRS)

Barritt, Brian; Bhasin, Kul; Eddy, Wesley; Matthews, Seth

2010-01-01

Network simulator software tools are often used to model the behaviors and interactions of applications, protocols, packets, and data links in terrestrial communication networks. Other software tools that model the physics, orbital dynamics, and RF characteristics of space systems have matured to allow for rapid, detailed analysis of space communication links. However, the absence of a unified toolset that integrates the two modeling approaches has encumbered the systems engineers tasked with the design, architecture, and analysis of complex space communication networks and systems. This paper presents the unified approach and describes the motivation, challenges, and our solution - the customization of the network simulator to integrate with astronautical analysis software tools for high-fidelity end-to-end simulation. Keywords space; communication; systems; networking; simulation; modeling; QualNet; STK; integration; space networks

Automated Quantification and Integrative Analysis of 2D and 3D Mitochondrial Shape and Network Properties

PubMed Central

Nikolaisen, Julie; Nilsson, Linn I. H.; Pettersen, Ina K. N.; Willems, Peter H. G. M.; Lorens, James B.; Koopman, Werner J. H.; Tronstad, Karl J.

2014-01-01

Mitochondrial morphology and function are coupled in healthy cells, during pathological conditions and (adaptation to) endogenous and exogenous stress. In this sense mitochondrial shape can range from small globular compartments to complex filamentous networks, even within the same cell. Understanding how mitochondrial morphological changes (i.e. “mitochondrial dynamics”) are linked to cellular (patho) physiology is currently the subject of intense study and requires detailed quantitative information. During the last decade, various computational approaches have been developed for automated 2-dimensional (2D) analysis of mitochondrial morphology and number in microscopy images. Although these strategies are well suited for analysis of adhering cells with a flat morphology they are not applicable for thicker cells, which require a three-dimensional (3D) image acquisition and analysis procedure. Here we developed and validated an automated image analysis algorithm allowing simultaneous 3D quantification of mitochondrial morphology and network properties in human endothelial cells (HUVECs). Cells expressing a mitochondria-targeted green fluorescence protein (mitoGFP) were visualized by 3D confocal microscopy and mitochondrial morphology was quantified using both the established 2D method and the new 3D strategy. We demonstrate that both analyses can be used to characterize and discriminate between various mitochondrial morphologies and network properties. However, the results from 2D and 3D analysis were not equivalent when filamentous mitochondria in normal HUVECs were compared with circular/spherical mitochondria in metabolically stressed HUVECs treated with rotenone (ROT). 2D quantification suggested that metabolic stress induced mitochondrial fragmentation and loss of biomass. In contrast, 3D analysis revealed that the mitochondrial network structure was dissolved without affecting the amount and size of the organelles. Thus, our results demonstrate that 3D imaging and quantification are crucial for proper understanding of mitochondrial shape and topology in non-flat cells. In summary, we here present an integrative method for unbiased 3D quantification of mitochondrial shape and network properties in mammalian cells. PMID:24988307

Using CODAP Job Analysis for the Development of Integrated Training Requirements for Three Army Civilian Career Fields.

ERIC Educational Resources Information Center

Fisher, Gerald P.; And Others

A multiuse Comprehensive Occupational Data Analysis Program (CODAP) job analysis is being used to develop training requirements and selection criteria for three interrelated Army civilian logistics career fields. Individual job task lists for the 20 job series within the three career programs were developed. The lists were based on a review of…

A collection of public transport network data sets for 25 cities

PubMed Central

Kujala, Rainer; Weckström, Christoffer; Darst, Richard K.; Mladenović, Miloš N; Saramäki, Jari

2018-01-01

Various public transport (PT) agencies publish their route and timetable information with the General Transit Feed Specification (GTFS) as the standard open format. Timetable data are commonly used for PT passenger routing. They can also be used for studying the structure and organization of PT networks, as well as the accessibility and the level of service these networks provide. However, using raw GTFS data is challenging as researchers need to understand the details of the GTFS data format, make sure that the data contain all relevant modes of public transport, and have no errors. To lower the barrier for using GTFS data in research, we publish a curated collection of 25 cities' public transport networks in multiple easy-to-use formats including network edge lists, temporal network event lists, SQLite databases, GeoJSON files, and the GTFS data format. This collection promotes the study of how PT is organized across the globe, and also provides a testbed for developing tools for PT network analysis and PT routing algorithms. PMID:29762553

Systematic Review of Integrative Health Care Research: Randomized Control Trials, Clinical Controlled Trials, and Meta-Analysis

PubMed Central

Khorsan, Raheleh; Coulter, Ian D.; Crawford, Cindy; Hsiao, An-Fu

2011-01-01

A systematic review was conducted to assess the level of evidence for integrative health care research. We searched PubMed, Allied and Complementary Medicine (AMED), BIOSIS Previews, EMBASE, the entire Cochrane Library, MANTIS, Social SciSearch, SciSearch Cited Ref Sci, PsychInfo, CINAHL, and NCCAM grantee publications listings, from database inception to May 2009, as well as searches of the “gray literature.” Available studies published in English language were included. Three independent reviewers rated each article and assessed the methodological quality of studies using the Scottish Intercollegiate Guidelines Network (SIGN 50). Our search yielded 11,891 total citations but 6 clinical studies, including 4 randomized, met our inclusion criteria. There are no available systematic reviews/meta-analyses published that met our inclusion criteria. The methodological quality of the included studies was assessed independently using quality checklists of the SIGN 50. Only a small number of RCTs and CCTs with a limited number of patients and lack of adequate control groups assessing integrative health care research are available. These studies provide limited evidence of effective integrative health care on some modalities. However, integrative health care regimen appears to be generally safe. PMID:20953383

GLOBECOM '85 - Global Telecommunications Conference, New Orleans, LA, December 2-5, 1985, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

Various papers on global telecommunications are presented. The general topics addressed include: multiservice integration with optical fibers, multicompany owned telecommunication networks, softworks quality and reliability, advanced on-board processing, impact of new services and systems on operations and maintenance, analytical studies of protocols for data communication networks, topics in packet radio networking, CCITT No. 7 to support new services, document processing and communication, antenna technology and system aspects in satellite communications. Also considered are: communication systems modelling methodology, experimental integrated local area voice/data nets, spread spectrum communications, motion video at the DS-0 rate, optical and data communications, intelligent work stations, switch performance analysis, novel radio communication systems, wireless local networks, ISDN services, LAN communication protocols, user-system interface, radio propagation and performance, mobile satellite system, software for computer networks, VLSI for ISDN terminals, quality management, man-machine interfaces in switching, and local area network performance.

Extensive cross-talk and global regulators identified from an analysis of the integrated transcriptional and signaling network in Escherichia coli.

PubMed

Antiqueira, Lucas; Janga, Sarath Chandra; Costa, Luciano da Fontoura

2012-11-01

To understand the regulatory dynamics of transcription factors (TFs) and their interplay with other cellular components we have integrated transcriptional, protein-protein and the allosteric or equivalent interactions which mediate the physiological activity of TFs in Escherichia coli. To study this integrated network we computed a set of network measurements followed by principal component analysis (PCA), investigated the correlations between network structure and dynamics, and carried out a procedure for motif detection. In particular, we show that outliers identified in the integrated network based on their network properties correspond to previously characterized global transcriptional regulators. Furthermore, outliers are highly and widely expressed across conditions, thus supporting their global nature in controlling many genes in the cell. Motifs revealed that TFs not only interact physically with each other but also obtain feedback from signals delivered by signaling proteins supporting the extensive cross-talk between different types of networks. Our analysis can lead to the development of a general framework for detecting and understanding global regulatory factors in regulatory networks and reinforces the importance of integrating multiple types of interactions in underpinning the interrelationships between them.

Functional Integration

NASA Astrophysics Data System (ADS)

Cartier, Pierre; DeWitt-Morette, Cecile

2006-11-01

Acknowledgements; List symbols, conventions, and formulary; Part I. The Physical and Mathematical Environment: 1. The physical and mathematical environment; Part II. Quantum Mechanics: 2. First lesson: gaussian integrals; 3. Selected examples; 4. Semiclassical expansion: WKB; 5. Semiclassical expansion: beyond WKB; 6. Quantum dynamics: path integrals and operator formalism; Part III. Methods from Differential Geometry: 7. Symmetries; 8. Homotopy; 9. Grassmann analysis: basics; 10. Grassmann analysis: applications; 11. Volume elements, divergences, gradients; Part IV. Non-Gaussian Applications: 12. Poisson processes in physics; 13. A mathematical theory of Poisson processes; 14. First exit time: energy problems; Part V. Problems in Quantum Field Theory: 15. Renormalization 1: an introduction; 16. Renormalization 2: scaling; 17. Renormalization 3: combinatorics; 18. Volume elements in quantum field theory Bryce DeWitt; Part VI. Projects: 19. Projects; Appendix A. Forward and backward integrals: spaces of pointed paths; Appendix B. Product integrals; Appendix C. A compendium of gaussian integrals; Appendix D. Wick calculus Alexander Wurm; Appendix E. The Jacobi operator; Appendix F. Change of variables of integration; Appendix G. Analytic properties of covariances; Appendix H. Feynman's checkerboard; Bibliography; Index.

Functional Integration

NASA Astrophysics Data System (ADS)

Cartier, Pierre; DeWitt-Morette, Cecile

2010-06-01

Acknowledgements; List symbols, conventions, and formulary; Part I. The Physical and Mathematical Environment: 1. The physical and mathematical environment; Part II. Quantum Mechanics: 2. First lesson: gaussian integrals; 3. Selected examples; 4. Semiclassical expansion: WKB; 5. Semiclassical expansion: beyond WKB; 6. Quantum dynamics: path integrals and operator formalism; Part III. Methods from Differential Geometry: 7. Symmetries; 8. Homotopy; 9. Grassmann analysis: basics; 10. Grassmann analysis: applications; 11. Volume elements, divergences, gradients; Part IV. Non-Gaussian Applications: 12. Poisson processes in physics; 13. A mathematical theory of Poisson processes; 14. First exit time: energy problems; Part V. Problems in Quantum Field Theory: 15. Renormalization 1: an introduction; 16. Renormalization 2: scaling; 17. Renormalization 3: combinatorics; 18. Volume elements in quantum field theory Bryce DeWitt; Part VI. Projects: 19. Projects; Appendix A. Forward and backward integrals: spaces of pointed paths; Appendix B. Product integrals; Appendix C. A compendium of gaussian integrals; Appendix D. Wick calculus Alexander Wurm; Appendix E. The Jacobi operator; Appendix F. Change of variables of integration; Appendix G. Analytic properties of covariances; Appendix H. Feynman's checkerboard; Bibliography; Index.

Critical assessment of human metabolic pathway databases: a stepping stone for future integration

PubMed Central

2011-01-01

Background Multiple pathway databases are available that describe the human metabolic network and have proven their usefulness in many applications, ranging from the analysis and interpretation of high-throughput data to their use as a reference repository. However, so far the various human metabolic networks described by these databases have not been systematically compared and contrasted, nor has the extent to which they differ been quantified. For a researcher using these databases for particular analyses of human metabolism, it is crucial to know the extent of the differences in content and their underlying causes. Moreover, the outcomes of such a comparison are important for ongoing integration efforts. Results We compared the genes, EC numbers and reactions of five frequently used human metabolic pathway databases. The overlap is surprisingly low, especially on reaction level, where the databases agree on 3% of the 6968 reactions they have combined. Even for the well-established tricarboxylic acid cycle the databases agree on only 5 out of the 30 reactions in total. We identified the main causes for the lack of overlap. Importantly, the databases are partly complementary. Other explanations include the number of steps a conversion is described in and the number of possible alternative substrates listed. Missing metabolite identifiers and ambiguous names for metabolites also affect the comparison. Conclusions Our results show that each of the five networks compared provides us with a valuable piece of the puzzle of the complete reconstruction of the human metabolic network. To enable integration of the networks, next to a need for standardizing the metabolite names and identifiers, the conceptual differences between the databases should be resolved. Considerable manual intervention is required to reach the ultimate goal of a unified and biologically accurate model for studying the systems biology of human metabolism. Our comparison provides a stepping stone for such an endeavor. PMID:21999653

VirtualPlant: A Software Platform to Support Systems Biology Research1[W][OA

PubMed Central

Katari, Manpreet S.; Nowicki, Steve D.; Aceituno, Felipe F.; Nero, Damion; Kelfer, Jonathan; Thompson, Lee Parnell; Cabello, Juan M.; Davidson, Rebecca S.; Goldberg, Arthur P.; Shasha, Dennis E.; Coruzzi, Gloria M.; Gutiérrez, Rodrigo A.

2010-01-01

Data generation is no longer the limiting factor in advancing biological research. In addition, data integration, analysis, and interpretation have become key bottlenecks and challenges that biologists conducting genomic research face daily. To enable biologists to derive testable hypotheses from the increasing amount of genomic data, we have developed the VirtualPlant software platform. VirtualPlant enables scientists to visualize, integrate, and analyze genomic data from a systems biology perspective. VirtualPlant integrates genome-wide data concerning the known and predicted relationships among genes, proteins, and molecules, as well as genome-scale experimental measurements. VirtualPlant also provides visualization techniques that render multivariate information in visual formats that facilitate the extraction of biological concepts. Importantly, VirtualPlant helps biologists who are not trained in computer science to mine lists of genes, microarray experiments, and gene networks to address questions in plant biology, such as: What are the molecular mechanisms by which internal or external perturbations affect processes controlling growth and development? We illustrate the use of VirtualPlant with three case studies, ranging from querying a gene of interest to the identification of gene networks and regulatory hubs that control seed development. Whereas the VirtualPlant software was developed to mine Arabidopsis (Arabidopsis thaliana) genomic data, its data structures, algorithms, and visualization tools are designed in a species-independent way. VirtualPlant is freely available at www.virtualplant.org. PMID:20007449

Maintaining the Database for Information Object Analysis, Intent, Dissemination and Enhancement (IOAIDE) and the US Army Research Laboratory Campus Sensor Network (ARL CSN)

DTIC Science & Technology

2017-01-01

CII-B 2800 Powder Mill Road Adelphi, MD 20783-1138 8. PERFORMING ORGANIZATION REPORT NUMBER ARL-TR-7921 9. SPONSORING/MONITORING AGENCY NAME(S...server database, structured query language, information objects, instructions, maintenance , cursor on target events, unattended ground sensors...unlimited. iii Contents List of Figures iv 1. Introduction 1 2. Computer and Software Development Tools Requirements 1 3. Database Maintenance 2 3.1

Network Directory. The Network of Colleges and Universities Committed to the Elimination of Drug and Alcohol Abuse.

ERIC Educational Resources Information Center

Clement, Vonnie

This directory lists the over 1,500 members of the Network of Colleges and Universities Committed to the Elimination of Drug and Alcohol Abuse. The member colleges and universities are listed by state and within each state section listed alphabetically by institution. The listings show addresses, institution presidents, and contact persons with…

Bayesian networks for satellite payload testing

NASA Astrophysics Data System (ADS)

Przytula, Krzysztof W.; Hagen, Frank; Yung, Kar

1999-11-01

Satellite payloads are fast increasing in complexity, resulting in commensurate growth in cost of manufacturing and operation. A need exists for a software tool, which would assist engineers in production and operation of satellite systems. We have designed and implemented a software tool, which performs part of this task. The tool aids a test engineer in debugging satellite payloads during system testing. At this stage of satellite integration and testing both the tested payload and the testing equipment represent complicated systems consisting of a very large number of components and devices. When an error is detected during execution of a test procedure, the tool presents to the engineer a ranked list of potential sources of the error and a list of recommended further tests. The engineer decides this on this basis if to perform some of the recommended additional test or replace the suspect component. The tool has been installed in payload testing facility. The tool is based on Bayesian networks, a graphical method of representing uncertainty in terms of probabilistic influences. The Bayesian network was configured using detailed flow diagrams of testing procedures and block diagrams of the payload and testing hardware. The conditional and prior probability values were initially obtained from experts and refined in later stages of design. The Bayesian network provided a very informative model of the payload and testing equipment and inspired many new ideas regarding the future test procedures and testing equipment configurations. The tool is the first step in developing a family of tools for various phases of satellite integration and operation.

P185-M Protein Identification and Validation of Results in Workflows that Integrate over Various Instruments, Datasets, Search Engines

PubMed Central

Hufnagel, P.; Glandorf, J.; Körting, G.; Jabs, W.; Schweiger-Hufnagel, U.; Hahner, S.; Lubeck, M.; Suckau, D.

2007-01-01

Analysis of complex proteomes often results in long protein lists, but falls short in measuring the validity of identification and quantification results on a greater number of proteins. Biological and technical replicates are mandatory, as is the combination of the MS data from various workflows (gels, 1D-LC, 2D-LC), instruments (TOF/TOF, trap, qTOF or FTMS), and search engines. We describe a database-driven study that combines two workflows, two mass spectrometers, and four search engines with protein identification following a decoy database strategy. The sample was a tryptically digested lysate (10,000 cells) of a human colorectal cancer cell line. Data from two LC-MALDI-TOF/TOF runs and a 2D-LC-ESI-trap run using capillary and nano-LC columns were submitted to the proteomics software platform ProteinScape. The combined MALDI data and the ESI data were searched using Mascot (Matrix Science), Phenyx (GeneBio), ProteinSolver (Bruker and Protagen), and Sequest (Thermo) against a decoy database generated from IPI-human in order to obtain one protein list across all workflows and search engines at a defined maximum false-positive rate of 5%. ProteinScape combined the data to one LC-MALDI and one LC-ESI dataset. The initial separate searches from the two combined datasets generated eight independent peptide lists. These were compiled into an integrated protein list using the ProteinExtractor algorithm. An initial evaluation of the generated data led to the identification of approximately 1200 proteins. Result integration on a peptide level allowed discrimination of protein isoforms that would not have been possible with a mere combination of protein lists.

Systems Biology Approaches for Discovering Biomarkers for Traumatic Brain Injury

PubMed Central

Feala, Jacob D.; AbdulHameed, Mohamed Diwan M.; Yu, Chenggang; Dutta, Bhaskar; Yu, Xueping; Schmid, Kara; Dave, Jitendra; Tortella, Frank

2013-01-01

Abstract The rate of traumatic brain injury (TBI) in service members with wartime injuries has risen rapidly in recent years, and complex, variable links have emerged between TBI and long-term neurological disorders. The multifactorial nature of TBI secondary cellular response has confounded attempts to find cellular biomarkers for its diagnosis and prognosis or for guiding therapy for brain injury. One possibility is to apply emerging systems biology strategies to holistically probe and analyze the complex interweaving molecular pathways and networks that mediate the secondary cellular response through computational models that integrate these diverse data sets. Here, we review available systems biology strategies, databases, and tools. In addition, we describe opportunities for applying this methodology to existing TBI data sets to identify new biomarker candidates and gain insights about the underlying molecular mechanisms of TBI response. As an exemplar, we apply network and pathway analysis to a manually compiled list of 32 protein biomarker candidates from the literature, recover known TBI-related mechanisms, and generate hypothetical new biomarker candidates. PMID:23510232

An integrated strategy to improve data acquisition and metabolite identification by time-staggered ion lists in UHPLC/Q-TOF MS-based metabolomics.

PubMed

Wang, Yang; Feng, Ruibing; He, Chengwei; Su, Huanxing; Ma, Huan; Wan, Jian-Bo

2018-08-05

The narrow linear range and the limited scan time of the given ion make the quantification of the features challenging in liquid chromatography-mass spectrometry (LC-MS)-based untargeted metabolomics with the full-scan mode. And metabolite identification is another bottleneck of untargeted analysis owing to the difficulty of acquiring MS/MS information of most metabolites detected. In this study, an integrated workflow was proposed using the newly established multiple ion monitoring mode with time-staggered ion lists (tsMIM) and target-directed data-dependent acquisition with time-staggered ion lists (tsDDA) to improve data acquisition and metabolite identification in UHPLC/Q-TOF MS-based untargeted metabolomics. Compared to the conventional untargeted metabolomics, the proprosed workflow exhibited the better repeatability before and after data normalization. After selecting features with the significant change by statistical analysis, MS/MS information of all these features can be obtained by tsDDA analysis to facilitate metabolite identification. Using time-staggered ion lists, the workflow is more sensitive in data acquisition, especially for the low-abundant features. Moreover, the metabolites with low abundance tend to be wrongly integrated and triggered by full scan-based untargeted analysis with MS E acquisition mode, which can be greatly improved by the proposed workflow. The integrated workflow was also successfully applied to discover serum biosignatures for the genetic modification of fat-1 in mice, which indicated its practicability and great potential in future metabolomics studies. Copyright © 2018 Elsevier B.V. All rights reserved.

A Planning Guide for Instructional Networks, Part I.

ERIC Educational Resources Information Center

Daly, Kevin F.

1994-01-01

Discusses three phases in implementing a master plan for a school-based local area network (LAN): (1) network software selection; (2) hardware selection, network topology, and site preparation; and (3) implementation time table. Sample planning and specification worksheets and a list of planning guides are included. (Contains six references.) (KRN)

Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data.

PubMed

Tomescu, Oana A; Mattanovich, Diethard; Thallinger, Gerhard G

2014-01-01

Technological improvements have shifted the focus from data generation to data analysis. The availability of large amounts of data from transcriptomics, protemics and metabolomics experiments raise new questions concerning suitable integrative analysis methods. We compare three integrative analysis techniques (co-inertia analysis, generalized singular value decomposition and integrative biclustering) by applying them to gene and protein abundance data from the six life cycle stages of Plasmodium falciparum. Co-inertia analysis is an analysis method used to visualize and explore gene and protein data. The generalized singular value decomposition has shown its potential in the analysis of two transcriptome data sets. Integrative Biclustering applies biclustering to gene and protein data. Using CIA, we visualize the six life cycle stages of Plasmodium falciparum, as well as GO terms in a 2D plane and interpret the spatial configuration. With GSVD, we decompose the transcriptomic and proteomic data sets into matrices with biologically meaningful interpretations and explore the processes captured by the data sets. IBC identifies groups of genes, proteins, GO Terms and life cycle stages of Plasmodium falciparum. We show method-specific results as well as a network view of the life cycle stages based on the results common to all three methods. Additionally, by combining the results of the three methods, we create a three-fold validated network of life cycle stage specific GO terms: Sporozoites are associated with transcription and transport; merozoites with entry into host cell as well as biosynthetic and metabolic processes; rings with oxidation-reduction processes; trophozoites with glycolysis and energy production; schizonts with antigenic variation and immune response; gametocyctes with DNA packaging and mitochondrial transport. Furthermore, the network connectivity underlines the separation of the intraerythrocytic cycle from the gametocyte and sporozoite stages. Using integrative analysis techniques, we can integrate knowledge from different levels and obtain a wider view of the system under study. The overlap between method-specific and common results is considerable, even if the basic mathematical assumptions are very different. The three-fold validated network of life cycle stage characteristics of Plasmodium falciparum could identify a large amount of the known associations from literature in only one study.

Integrative omics analysis. A study based on Plasmodium falciparum mRNA and protein data

PubMed Central

2014-01-01

Background Technological improvements have shifted the focus from data generation to data analysis. The availability of large amounts of data from transcriptomics, protemics and metabolomics experiments raise new questions concerning suitable integrative analysis methods. We compare three integrative analysis techniques (co-inertia analysis, generalized singular value decomposition and integrative biclustering) by applying them to gene and protein abundance data from the six life cycle stages of Plasmodium falciparum. Co-inertia analysis is an analysis method used to visualize and explore gene and protein data. The generalized singular value decomposition has shown its potential in the analysis of two transcriptome data sets. Integrative Biclustering applies biclustering to gene and protein data. Results Using CIA, we visualize the six life cycle stages of Plasmodium falciparum, as well as GO terms in a 2D plane and interpret the spatial configuration. With GSVD, we decompose the transcriptomic and proteomic data sets into matrices with biologically meaningful interpretations and explore the processes captured by the data sets. IBC identifies groups of genes, proteins, GO Terms and life cycle stages of Plasmodium falciparum. We show method-specific results as well as a network view of the life cycle stages based on the results common to all three methods. Additionally, by combining the results of the three methods, we create a three-fold validated network of life cycle stage specific GO terms: Sporozoites are associated with transcription and transport; merozoites with entry into host cell as well as biosynthetic and metabolic processes; rings with oxidation-reduction processes; trophozoites with glycolysis and energy production; schizonts with antigenic variation and immune response; gametocyctes with DNA packaging and mitochondrial transport. Furthermore, the network connectivity underlines the separation of the intraerythrocytic cycle from the gametocyte and sporozoite stages. Conclusion Using integrative analysis techniques, we can integrate knowledge from different levels and obtain a wider view of the system under study. The overlap between method-specific and common results is considerable, even if the basic mathematical assumptions are very different. The three-fold validated network of life cycle stage characteristics of Plasmodium falciparum could identify a large amount of the known associations from literature in only one study. PMID:25033389

Space Communications and Navigation (SCaN) Network Simulation Tool Development and Its Use Cases

NASA Technical Reports Server (NTRS)

Jennings, Esther; Borgen, Richard; Nguyen, Sam; Segui, John; Stoenescu, Tudor; Wang, Shin-Ywan; Woo, Simon; Barritt, Brian; Chevalier, Christine; Eddy, Wesley

2009-01-01

In this work, we focus on the development of a simulation tool to assist in analysis of current and future (proposed) network architectures for NASA. Specifically, the Space Communications and Navigation (SCaN) Network is being architected as an integrated set of new assets and a federation of upgraded legacy systems. The SCaN architecture for the initial missions for returning humans to the moon and beyond will include the Space Network (SN) and the Near-Earth Network (NEN). In addition to SCaN, the initial mission scenario involves a Crew Exploration Vehicle (CEV), the International Space Station (ISS) and NASA Integrated Services Network (NISN). We call the tool being developed the SCaN Network Integration and Engineering (SCaN NI&E) Simulator. The intended uses of such a simulator are: (1) to characterize performance of particular protocols and configurations in mission planning phases; (2) to optimize system configurations by testing a larger parameter space than may be feasible in either production networks or an emulated environment; (3) to test solutions in order to find issues/risks before committing more significant resources needed to produce real hardware or flight software systems. We describe two use cases of the tool: (1) standalone simulation of CEV to ISS baseline scenario to determine network performance, (2) participation in Distributed Simulation Integration Laboratory (DSIL) tests to perform function testing and verify interface and interoperability of geographically dispersed simulations/emulations.

Shared molecular pathways and gene networks for cardiovascular disease and type 2 diabetes mellitus in women across diverse ethnicities.

PubMed

Chan, Kei Hang K; Huang, Yen-Tsung; Meng, Qingying; Wu, Chunyuan; Reiner, Alexander; Sobel, Eric M; Tinker, Lesley; Lusis, Aldons J; Yang, Xia; Liu, Simin

2014-12-01

Although cardiovascular disease (CVD) and type 2 diabetes mellitus (T2D) share many common risk factors, potential molecular mechanisms that may also be shared for these 2 disorders remain unknown. Using an integrative pathway and network analysis, we performed genome-wide association studies in 8155 blacks, 3494 Hispanic American, and 3697 Caucasian American women who participated in the national Women's Health Initiative single-nucleotide polymorphism (SNP) Health Association Resource and the Genomics and Randomized Trials Network. Eight top pathways and gene networks related to cardiomyopathy, calcium signaling, axon guidance, cell adhesion, and extracellular matrix seemed to be commonly shared between CVD and T2D across all 3 ethnic groups. We also identified ethnicity-specific pathways, such as cell cycle (specific for Hispanic American and Caucasian American) and tight junction (CVD and combined CVD and T2D in Hispanic American). In network analysis of gene-gene or protein-protein interactions, we identified key drivers that included COL1A1, COL3A1, and ELN in the shared pathways for both CVD and T2D. These key driver genes were cross-validated in multiple mouse models of diabetes mellitus and atherosclerosis. Our integrative analysis of American women of 3 ethnicities identified multiple shared biological pathways and key regulatory genes for the development of CVD and T2D. These prospective findings also support the notion that ethnicity-specific susceptibility genes and process are involved in the pathogenesis of CVD and T2D. © 2014 American Heart Association, Inc.

Functional Module Search in Protein Networks based on Semantic Similarity Improves the Analysis of Proteomics Data*

PubMed Central

Boyanova, Desislava; Nilla, Santosh; Klau, Gunnar W.; Dandekar, Thomas; Müller, Tobias; Dittrich, Marcus

2014-01-01

The continuously evolving field of proteomics produces increasing amounts of data while improving the quality of protein identifications. Albeit quantitative measurements are becoming more popular, many proteomic studies are still based on non-quantitative methods for protein identification. These studies result in potentially large sets of identified proteins, where the biological interpretation of proteins can be challenging. Systems biology develops innovative network-based methods, which allow an integrated analysis of these data. Here we present a novel approach, which combines prior knowledge of protein-protein interactions (PPI) with proteomics data using functional similarity measurements of interacting proteins. This integrated network analysis exactly identifies network modules with a maximal consistent functional similarity reflecting biological processes of the investigated cells. We validated our approach on small (H9N2 virus-infected gastric cells) and large (blood constituents) proteomic data sets. Using this novel algorithm, we identified characteristic functional modules in virus-infected cells, comprising key signaling proteins (e.g. the stress-related kinase RAF1) and demonstrate that this method allows a module-based functional characterization of cell types. Analysis of a large proteome data set of blood constituents resulted in clear separation of blood cells according to their developmental origin. A detailed investigation of the T-cell proteome further illustrates how the algorithm partitions large networks into functional subnetworks each representing specific cellular functions. These results demonstrate that the integrated network approach not only allows a detailed analysis of proteome networks but also yields a functional decomposition of complex proteomic data sets and thereby provides deeper insights into the underlying cellular processes of the investigated system. PMID:24807868

MIR@NT@N: a framework integrating transcription factors, microRNAs and their targets to identify sub-network motifs in a meta-regulation network model

PubMed Central

2011-01-01

Background To understand biological processes and diseases, it is crucial to unravel the concerted interplay of transcription factors (TFs), microRNAs (miRNAs) and their targets within regulatory networks and fundamental sub-networks. An integrative computational resource generating a comprehensive view of these regulatory molecular interactions at a genome-wide scale would be of great interest to biologists, but is not available to date. Results To identify and analyze molecular interaction networks, we developed MIR@NT@N, an integrative approach based on a meta-regulation network model and a large-scale database. MIR@NT@N uses a graph-based approach to predict novel molecular actors across multiple regulatory processes (i.e. TFs acting on protein-coding or miRNA genes, or miRNAs acting on messenger RNAs). Exploiting these predictions, the user can generate networks and further analyze them to identify sub-networks, including motifs such as feedback and feedforward loops (FBL and FFL). In addition, networks can be built from lists of molecular actors with an a priori role in a given biological process to predict novel and unanticipated interactions. Analyses can be contextualized and filtered by integrating additional information such as microarray expression data. All results, including generated graphs, can be visualized, saved and exported into various formats. MIR@NT@N performances have been evaluated using published data and then applied to the regulatory program underlying epithelium to mesenchyme transition (EMT), an evolutionary-conserved process which is implicated in embryonic development and disease. Conclusions MIR@NT@N is an effective computational approach to identify novel molecular regulations and to predict gene regulatory networks and sub-networks including conserved motifs within a given biological context. Taking advantage of the M@IA environment, MIR@NT@N is a user-friendly web resource freely available at http://mironton.uni.lu which will be updated on a regular basis. PMID:21375730

A protein interaction network analysis for yeast integral membrane protein.

PubMed

Shi, Ming-Guang; Huang, De-Shuang; Li, Xue-Ling

2008-01-01

Although the yeast Saccharomyces cerevisiae is the best exemplified single-celled eukaryote, the vast number of protein-protein interactions of integral membrane proteins of Saccharomyces cerevisiae have not been characterized by experiments. Here, based on the kernel method of Greedy Kernel Principal Component analysis plus Linear Discriminant Analysis, we identify 300 protein-protein interactions involving 189 membrane proteins and get the outcome of a highly connected protein-protein interactions network. Furthermore, we study the global topological features of integral membrane proteins network of Saccharomyces cerevisiae. These results give the comprehensive description of protein-protein interactions of integral membrane proteins and reveal global topological and robustness of the interactome network at a system level. This work represents an important step towards a comprehensive understanding of yeast protein interactions.

Efficient Synthesis of Network Updates

DTIC Science & Technology

2015-06-17

model include switches S i , links L j , and a single controller element C, and a network N is a tuple containing these. Each switch S i is encoded as a...and the ports they should be forwarded to respec- tively. Each link L j is represented by a record consisting of two locations loc and loc0 and a list...the union of multisets m1 and m2. We write [x] for a singleton list, and l1@l2 for concatenation of l1 and l2. Each transition N o ! N 0 is anno - tated

UMA/GAN network architecture analysis

NASA Astrophysics Data System (ADS)

Yang, Liang; Li, Wensheng; Deng, Chunjian; Lv, Yi

2009-07-01

This paper is to critically analyze the architecture of UMA which is one of Fix Mobile Convergence (FMC) solutions, and also included by the third generation partnership project(3GPP). In UMA/GAN network architecture, UMA Network Controller (UNC) is the key equipment which connects with cellular core network and mobile station (MS). UMA network could be easily integrated into the existing cellular networks without influencing mobile core network, and could provides high-quality mobile services with preferentially priced indoor voice and data usage. This helps to improve subscriber's experience. On the other hand, UMA/GAN architecture helps to integrate other radio technique into cellular network which includes WiFi, Bluetooth, and WiMax and so on. This offers the traditional mobile operators an opportunity to integrate WiMax technique into cellular network. In the end of this article, we also give an analysis of potential influence on the cellular core networks ,which is pulled by UMA network.

The Plant Genome Integrative Explorer Resource: PlantGenIE.org.

PubMed

Sundell, David; Mannapperuma, Chanaka; Netotea, Sergiu; Delhomme, Nicolas; Lin, Yao-Cheng; Sjödin, Andreas; Van de Peer, Yves; Jansson, Stefan; Hvidsten, Torgeir R; Street, Nathaniel R

2015-12-01

Accessing and exploring large-scale genomics data sets remains a significant challenge to researchers without specialist bioinformatics training. We present the integrated PlantGenIE.org platform for exploration of Populus, conifer and Arabidopsis genomics data, which includes expression networks and associated visualization tools. Standard features of a model organism database are provided, including genome browsers, gene list annotation, Blast homology searches and gene information pages. Community annotation updating is supported via integration of WebApollo. We have produced an RNA-sequencing (RNA-Seq) expression atlas for Populus tremula and have integrated these data within the expression tools. An updated version of the ComPlEx resource for performing comparative plant expression analyses of gene coexpression network conservation between species has also been integrated. The PlantGenIE.org platform provides intuitive access to large-scale and genome-wide genomics data from model forest tree species, facilitating both community contributions to annotation improvement and tools supporting use of the included data resources to inform biological insight. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Organizational Analysis of Energy Manpower Requirements in the United States Navy

DTIC Science & Technology

2013-06-01

ix LIST OF FIGURES Figure 1.  A 1.5 Megawatt wind turbine set up at the Marine Corps Logistics Base in Barstow, CA. (From Flores, 2010...Figure 1. A 1.5 Megawatt wind turbine set up at the Marine Corps Logistics Base in Barstow, CA. (From Flores, 2010) 9 In an effort to capture...electronic and information warfare systems ) (h ) Network Engineering (including wireless networks, sensor networks, high speed data networking, and

Integration in primary community care networks (PCCNs): examination of governance, clinical, marketing, financial, and information infrastructures in a national demonstration project in Taiwan

PubMed Central

Lin, Blossom Yen-Ju

2007-01-01

Background Taiwan's primary community care network (PCCN) demonstration project, funded by the Bureau of National Health Insurance on March 2003, was established to discourage hospital shopping behavior of people and drive the traditional fragmented health care providers into cooperate care models. Between 2003 and 2005, 268 PCCNs were established. This study profiled the individual members in the PCCNs to study the nature and extent to which their network infrastructures have been integrated among the members (clinics and hospitals) within individual PCCNs. Methods The thorough questionnaire items, covering the network working infrastructures – governance, clinical, marketing, financial, and information integration in PCCNs, were developed with validity and reliability confirmed. One thousand five hundred and fifty-seven clinics that had belonged to PCCNs for more than one year, based on the 2003–2005 Taiwan Primary Community Care Network List, were surveyed by mail. Nine hundred and twenty-eight clinic members responded to the surveys giving a 59.6 % response rate. Results Overall, the PCCNs' members had higher involvement in the governance infrastructure, which was usually viewed as the most important for establishment of core values in PCCNs' organization design and management at the early integration stage. In addition, it found that there existed a higher extent of integration of clinical, marketing, and information infrastructures among the hospital-clinic member relationship than those among clinic members within individual PCCNs. The financial infrastructure was shown the least integrated relative to other functional infrastructures at the early stage of PCCN formation. Conclusion There was still room for better integrated partnerships, as evidenced by the great variety of relationships and differences in extent of integration in this study. In addition to provide how the network members have done for their initial work at the early stage of network forming in this study, the detailed surveyed items, the concepts proposed by the managerial and theoretical professionals, could be a guide for those health care providers who have willingness to turn their business into multi-organizations. PMID:17577422

Integration in primary community care networks (PCCNs): examination of governance, clinical, marketing, financial, and information infrastructures in a national demonstration project in Taiwan.

PubMed

Lin, Blossom Yen-Ju

2007-06-19

Taiwan's primary community care network (PCCN) demonstration project, funded by the Bureau of National Health Insurance on March 2003, was established to discourage hospital shopping behavior of people and drive the traditional fragmented health care providers into cooperate care models. Between 2003 and 2005, 268 PCCNs were established. This study profiled the individual members in the PCCNs to study the nature and extent to which their network infrastructures have been integrated among the members (clinics and hospitals) within individual PCCNs. The thorough questionnaire items, covering the network working infrastructures--governance, clinical, marketing, financial, and information integration in PCCNs, were developed with validity and reliability confirmed. One thousand five hundred and fifty-seven clinics that had belonged to PCCNs for more than one year, based on the 2003-2005 Taiwan Primary Community Care Network List, were surveyed by mail. Nine hundred and twenty-eight clinic members responded to the surveys giving a 59.6 % response rate. Overall, the PCCNs' members had higher involvement in the governance infrastructure, which was usually viewed as the most important for establishment of core values in PCCNs' organization design and management at the early integration stage. In addition, it found that there existed a higher extent of integration of clinical, marketing, and information infrastructures among the hospital-clinic member relationship than those among clinic members within individual PCCNs. The financial infrastructure was shown the least integrated relative to other functional infrastructures at the early stage of PCCN formation. There was still room for better integrated partnerships, as evidenced by the great variety of relationships and differences in extent of integration in this study. In addition to provide how the network members have done for their initial work at the early stage of network forming in this study, the detailed surveyed items, the concepts proposed by the managerial and theoretical professionals, could be a guide for those health care providers who have willingness to turn their business into multi-organizations.

Repery dziedzictwa geologicznego na Lubelszczyźnie / Position of geological heritage in the Lublin Region

NASA Astrophysics Data System (ADS)

Dolecki, Leopold

2012-12-01

A systematic inventorying of natural objects and entire areas where objects of inanimate nature occur is being conducted in various countries to a different extent. In Poland, an important part is played by the Institute of Environmental Protection of PAS, the Polish Geological Institute, the University of Science and Technology (AGH) in Kraków, and numerous scientific institutions of higher education. During the UNESCO conference in 1997, an initiative was undertaken to create the so-called geoparks, i.e., documentation sites and nature reserves, associated in a regional network with a common theme. Such a network concentrates on the wealth of inanimate nature which is worth protecting due to its unique scientific, educational, historic and tourist value. This network works for the idea of sustained development and should have the support of the local authorities and community. The European Association for the Conservation of the Geological Heritage (ProGeo) is the organisation which integrates the research work concerning geoprotection. It undertook thenetwork of geosites, named Global Geosites. The GEOSITES programme is coordinated by the IUGS in cooperation with the ProGeo Association. The decision to add a given object to the world list is made during a UNESCO World Heritage Committee Session. In Poland, a preliminary list has been prepared featuring geosites nominated for the European list. A relatively small number of geosites represent the Lublin Region on that list. The article presents those sites and proposes that several more objects of inanimate nature situated in the region be included in that classification.

A Network Analysis of the Economic Development Community of Ethiopia Part 2

DTIC Science & Technology

2012-10-15

complete model. Also, during the original data collection phase, we overlooked the Ethiopian Chamber of Commerce and MIDROC (http://www.midroc...individual’s social standing reinforces the conclusion that he is influential. Ayalew Zegeye is the president of the Addis Ababa Chamber of Commerce and...October 2012 13 References Addis Ababa Chamber of Commerce and Sectoral Associations is a site that lists influential members of the Ethiopian

A Network Analysis of the Economic Development Community of Ethiopia Part 2

DTIC Science & Technology

2012-10-15

more complete model. Also, during the original data collection phase, we overlooked the Ethiopian Chamber of Commerce and MIDROC (http://www.midroc...individual’s social standing reinforces the conclusion that he is influential. Ayalew Zegeye is the president of the Addis Ababa Chamber of Commerce and...October 2012 13 References Addis Ababa Chamber of Commerce and Sectoral Associations is a site that lists influential members of the

Implementing a Social Knowledge Networking (SKN) system to enable meaningful use of an EHR medication reconciliation system.

PubMed

Rangachari, Pavani

2018-01-01

Despite the regulatory impetus toward meaningful use of electronic health record (EHR) Medication Reconciliation (MedRec) to prevent medication errors during care transitions, hospital adherence has lagged for one chief reason: low physician engagement, stemming from lack of consensus about which physician is responsible for managing a patient's medication list. In October 2016, Augusta University received a 2-year grant from the Agency for Healthcare Research and Quality to implement a Social Knowledge Networking (SKN) system for enabling its health system (AU Health) to progress from "limited use" of EHR MedRec technology to "meaningful use." The hypothesis is that SKN would bring together a diverse group of practitioners, to facilitate tacit knowledge exchange on issues related to EHR MedRec, which in turn is expected to increase practitioners' engagement in addressing those issues and enable meaningful use of EHR. The specific aims are to examine: 1) user-engagement in the SKN system, and 2) associations between "SKN use" and "meaningful use" of EHR. The 2-year project uses an exploratory mixed-method design and consists of three phases: 1) development; 2) SKN implementation; and 3) analysis. Phase 1, completed in May 2017, sought to identify a comprehensive set of issues related to EHR MedRec from practitioners directly involved in the MedRec process. This process facilitated development of a "Reporting Tool" on issues related to EHR MedRec, which, along with an existing "SKN/Discussion Tool," was integrated into the EHR at AU Health. Phase 2 (launched in June 2017) involves implementing the EHR-integrated SKN system over a 52-week period in inpatient and outpatient medicine units. The prospective implementation design is expected to generate context-sensitive strategies for meaningful use and successful implementation of EHR MedRec and thereby make substantial contributions to the patient safety and risk management literature. From a health care policy perspective, if the hypothesis holds, federal vendors could be encouraged to incorporate SKN features into EHR systems.

BoolNet--an R package for generation, reconstruction and analysis of Boolean networks.

PubMed

Müssel, Christoph; Hopfensitz, Martin; Kestler, Hans A

2010-05-15

As the study of information processing in living cells moves from individual pathways to complex regulatory networks, mathematical models and simulation become indispensable tools for analyzing the complex behavior of such networks and can provide deep insights into the functioning of cells. The dynamics of gene expression, for example, can be modeled with Boolean networks (BNs). These are mathematical models of low complexity, but have the advantage of being able to capture essential properties of gene-regulatory networks. However, current implementations of BNs only focus on different sub-aspects of this model and do not allow for a seamless integration into existing preprocessing pipelines. BoolNet efficiently integrates methods for synchronous, asynchronous and probabilistic BNs. This includes reconstructing networks from time series, generating random networks, robustness analysis via perturbation, Markov chain simulations, and identification and visualization of attractors. The package BoolNet is freely available from the R project at http://cran.r-project.org/ or http://www.informatik.uni-ulm.de/ni/mitarbeiter/HKestler/boolnet/ under Artistic License 2.0. hans.kestler@uni-ulm.de Supplementary data are available at Bioinformatics online.

CoryneRegNet 4.0 – A reference database for corynebacterial gene regulatory networks

PubMed Central

Baumbach, Jan

2007-01-01

Background Detailed information on DNA-binding transcription factors (the key players in the regulation of gene expression) and on transcriptional regulatory interactions of microorganisms deduced from literature-derived knowledge, computer predictions and global DNA microarray hybridization experiments, has opened the way for the genome-wide analysis of transcriptional regulatory networks. The large-scale reconstruction of these networks allows the in silico analysis of cell behavior in response to changing environmental conditions. We previously published CoryneRegNet, an ontology-based data warehouse of corynebacterial transcription factors and regulatory networks. Initially, it was designed to provide methods for the analysis and visualization of the gene regulatory network of Corynebacterium glutamicum. Results Now we introduce CoryneRegNet release 4.0, which integrates data on the gene regulatory networks of 4 corynebacteria, 2 mycobacteria and the model organism Escherichia coli K12. As the previous versions, CoryneRegNet provides a web-based user interface to access the database content, to allow various queries, and to support the reconstruction, analysis and visualization of regulatory networks at different hierarchical levels. In this article, we present the further improved database content of CoryneRegNet along with novel analysis features. The network visualization feature GraphVis now allows the inter-species comparisons of reconstructed gene regulatory networks and the projection of gene expression levels onto that networks. Therefore, we added stimulon data directly into the database, but also provide Web Service access to the DNA microarray analysis platform EMMA. Additionally, CoryneRegNet now provides a SOAP based Web Service server, which can easily be consumed by other bioinformatics software systems. Stimulons (imported from the database, or uploaded by the user) can be analyzed in the context of known transcriptional regulatory networks to predict putative contradictions or further gene regulatory interactions. Furthermore, it integrates protein clusters by means of heuristically solving the weighted graph cluster editing problem. In addition, it provides Web Service based access to up to date gene annotation data from GenDB. Conclusion The release 4.0 of CoryneRegNet is a comprehensive system for the integrated analysis of procaryotic gene regulatory networks. It is a versatile systems biology platform to support the efficient and large-scale analysis of transcriptional regulation of gene expression in microorganisms. It is publicly available at . PMID:17986320

Integrated expression analysis identifies transcription networks in mouse and human gastric neoplasia.

PubMed

Chen, Zheng; Soutto, Mohammed; Rahman, Bushra; Fazili, Muhammad W; Peng, DunFa; Blanca Piazuelo, Maria; Chen, Heidi; Kay Washington, M; Shyr, Yu; El-Rifai, Wael

2017-07-01

Gastric cancer (GC) is a leading cause of cancer-related deaths worldwide. The Tff1 knockout (KO) mouse model develops gastric lesions that include low-grade dysplasia (LGD), high-grade dysplasia (HGD), and adenocarcinomas. In this study, we used Affymetrix microarrays gene expression platforms for analysis of molecular signatures in the mouse stomach [Tff1-KO (LGD) and Tff1 wild-type (normal)] and human gastric cancer tissues and their adjacent normal tissue samples. Combined integrated bioinformatics analysis of mouse and human datasets indicated that 172 genes were consistently deregulated in both human gastric cancer samples and Tff1-KO LGD lesions (P < .05). Using Ingenuity pathway analysis, these genes mapped to important transcription networks that include MYC, STAT3, β-catenin, RELA, NFATC2, HIF1A, and ETS1 in both human and mouse. Further analysis demonstrated activation of FOXM1 and inhibition of TP53 transcription networks in human gastric cancers but not in Tff1-KO LGD lesions. Using real-time RT-PCR, we validated the deregulated expression of several genes (VCAM1, BGN, CLDN2, COL1A1, COL1A2, COL3A1, EpCAM, IFITM1, MMP9, MMP12, MMP14, PDGFRB, PLAU, and TIMP1) that map to altered transcription networks in both mouse and human gastric neoplasia. Our study demonstrates significant similarities in deregulated transcription networks in human gastric cancer and gastric tumorigenesis in the Tff1-KO mouse model. The data also suggest that activation of MYC, STAT3, RELA, and β-catenin transcription networks could be an early molecular step in gastric carcinogenesis. © 2017 Wiley Periodicals, Inc.

Biosensor for the detection of Listeria monocytogenes: emerging trends.

PubMed

Soni, Dharmendra Kumar; Ahmad, Rafiq; Dubey, Suresh Kumar

2018-05-23

The early detection of Listeria monocytogenes (L. monocytogenes) and understanding the disease burden is of paramount interest. The failure to detect pathogenic bacteria in the food industry may have terrible consequences, and poses deleterious effects on human health. Therefore, integration of methods to detect and trace the route of pathogens along the entire food supply network might facilitate elucidation of the main contamination sources. Recent research interest has been oriented towards the development of rapid and affordable pathogen detection tools/techniques. An innovative and new approach like biosensors has been quite promising in revealing the foodborne pathogens. In spite of the existing knowledge, advanced research is still needed to substantiate the expeditious nature and sensitivity of biosensors for rapid and in situ analysis of foodborne pathogens. This review summarizes recent developments in optical, piezoelectric, cell-based, and electrochemical biosensors for Listeria sp. detection in clinical diagnostics, food analysis, and environmental monitoring, and also lists their drawbacks and advantages.

Enhancing Knowledge Flow in a Health Care Context: A Mobile Computing Approach

PubMed Central

Souza, Diego Da Silva; de Lima, Patrícia Zudio; da Silveira, Pedro C; de Souza, Jano Moreira

2014-01-01

Background Advances in mobile computing and wireless communication have allowed people to interact and exchange knowledge almost anywhere. These technologies support Medicine 2.0, where the health knowledge flows among all involved people (eg, patients, caregivers, doctors, and patients’ relatives). Objective Our paper proposes a knowledge-sharing environment that takes advantage of mobile computing and contextual information to support knowledge sharing among participants within a health care community (ie, from patients to health professionals). This software environment enables knowledge exchange using peer-to-peer (P2P) mobile networks based on users’ profiles, and it facilitates face-to-face interactions among people with similar health interests, needs, or goals. Methods First, we reviewed and analyzed relevant scientific articles and software apps to determine the current state of knowledge flow within health care. Although no proposal was capable of addressing every aspect in the Medicine 2.0 paradigm, a list of requirements was compiled. Using this requirement list and our previous works, a knowledge-sharing environment was created integrating Mobile Exchange of Knowledge (MEK) and the Easy to Deploy Indoor Positioning System (EDIPS), and a twofold qualitative evaluation was performed. Second, we analyzed the efficiency and reliability of the knowledge that the integrated MEK-EDIPS tool provided to users according to their interest topics, and then performed a proof of concept with health professionals to determine the feasibility and usefulness of using this solution in a real-world scenario. Results . Using MEK, we reached 100% precision and 80% recall in the exchange of files within the peer-to-peer network. The mechanism that facilitated face-to-face interactions was evaluated by the difference between the location indicated by the EDIPS tool and the actual location of the people involved in the knowledge exchange. The average distance error was <6.28 m for an indoor environment. The usability and usefulness of this tool was assessed by questioning a sample of 18 health professionals: 94% (17/18) agreed the integrated MEK-EDIPS tool provides greater interaction among all the participants (eg, patients, caregivers, doctors, and patients’ relatives), most considered it extremely important in the health scenario, 72% (13/18) believed it could increase the knowledge flow in a health environment, and 67% (12/18) recommend it or would like to recommend its use. Conclusions The integrated MEK-EDIPS tool can provide more services than any other software tool analyzed in this paper. The proposed integrated MEK-EDIPS tool seems to be the best alternative for supporting health knowledge flow within the Medicine 2.0 paradigm. PMID:25427923

LINEBACkER: Bio-inspired Data Reduction Toward Real Time Network Traffic Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Teuton, Jeremy R.; Peterson, Elena S.; Nordwall, Douglas J.

Abstract—One essential component of resilient cyber applications is the ability to detect adversaries and protect systems with the same flexibility adversaries will use to achieve their goals. Current detection techniques do not enable this degree of flexibility because most existing applications are built using exact or regular-expression matching to libraries of rule sets. Further, network traffic defies traditional cyber security approaches that focus on limiting access based on the use of passwords and examination of lists of installed or downloaded programs. These approaches do not readily apply to network traffic occurring beyond the access control point, and when the datamore » in question are combined control and payload data of ever increasing speed and volume. Manual analysis of network traffic is not normally possible because of the magnitude of the data that is being exchanged and the length of time that this analysis takes. At the same time, using an exact matching scheme to identify malicious traffic in real time often fails because the lists against which such searches must operate grow too large. In this work, we introduce an alternative method for cyber network detection based on similarity-measuring algorithms for gene sequence analysis. These methods are ideal because they were designed to identify similar but nonidentical sequences. We demonstrate that our method is generally applicable to the problem of network traffic analysis by illustrating its use in two different areas both based on different attributes of network traffic. Our approach provides a logical framework for organizing large collections of network data, prioritizing traffic of interest to human analysts, and makes it possible to discover traffic signatures without the bias introduced by expert-directed signature generation. Pattern recognition on reduced representations of network traffic offers a fast, efficient, and more robust way to detect anomalies.« less

An Integrated Solution for Performing Thermo-fluid Conjugate Analysis

NASA Technical Reports Server (NTRS)

Kornberg, Oren

2009-01-01

A method has been developed which integrates a fluid flow analyzer and a thermal analyzer to produce both steady state and transient results of 1-D, 2-D, and 3-D analysis models. The Generalized Fluid System Simulation Program (GFSSP) is a one dimensional, general purpose fluid analysis code which computes pressures and flow distributions in complex fluid networks. The MSC Systems Improved Numerical Differencing Analyzer (MSC.SINDA) is a one dimensional general purpose thermal analyzer that solves network representations of thermal systems. Both GFSSP and MSC.SINDA have graphical user interfaces which are used to build the respective model and prepare it for analysis. The SINDA/GFSSP Conjugate Integrator (SGCI) is a formbase graphical integration program used to set input parameters for the conjugate analyses and run the models. The contents of this paper describes SGCI and its thermo-fluids conjugate analysis techniques and capabilities by presenting results from some example models including the cryogenic chill down of a copper pipe, a bar between two walls in a fluid stream, and a solid plate creating a phase change in a flowing fluid.

Network Access Control List Situation Awareness

ERIC Educational Resources Information Center

Reifers, Andrew

2010-01-01

Network security is a large and complex problem being addressed by multiple communities. Nevertheless, current theories in networking security appear to overestimate network administrators' ability to understand network access control lists (NACLs), providing few context specific user analyses. Consequently, the current research generally seems to…

A Lightweight Data Integrity Scheme for Sensor Networks

PubMed Central

Kamel, Ibrahim; Juma, Hussam

2011-01-01

Limited energy is the most critical constraint that limits the capabilities of wireless sensor networks (WSNs). Most sensors operate on batteries with limited power. Battery recharging or replacement may be impossible. Security mechanisms that are based on public key cryptographic algorithms such as RSA and digital signatures are prohibitively expensive in terms of energy consumption and storage requirements, and thus unsuitable for WSN applications. This paper proposes a new fragile watermarking technique to detect unauthorized alterations in WSN data streams. We propose the FWC-D scheme, which uses group delimiters to keep the sender and receivers synchronized and help them to avoid ambiguity in the event of data insertion or deletion. The watermark, which is computed using a hash function, is stored in the previous group in a linked-list fashion to ensure data freshness and mitigate replay attacks, FWC-D generates a serial number SN that is attached to each group to help the receiver determines how many group insertions or deletions occurred. Detailed security analysis that compares the proposed FWC-D scheme with SGW, one of the latest integrity schemes for WSNs, shows that FWC-D is more robust than SGW. Simulation results further show that the proposed scheme is much faster than SGW. PMID:22163840

The SPAN cookbook: A practical guide to accessing SPAN

NASA Technical Reports Server (NTRS)

Mason, Stephanie; Tencati, Ronald D.; Stern, David M.; Capps, Kimberly D.; Dorman, Gary; Peters, David J.

1990-01-01

This is a manual for remote users who wish to send electronic mail messages from the Space Physics Analysis Network (SPAN) to scientific colleagues on other computer networks and vice versa. In several instances more than one gateway has been included for the same network. Users are provided with an introduction to each network listed with helpful details about accessing the system and mail syntax examples. Also included is information on file transfers, remote logins, and help telephone numbers.

Houston Cole Library Collection Assessment.

ERIC Educational Resources Information Center

Henderson, William Abbot, Ed.; McAbee, Sonja L., Ed.

This document reports on an assessment of the Jacksonville State University's Houston Cole Library collection that employed a variety of methodologies and tools, including list-checking, direct collection examination, shelflist measurement and analysis, WLN (Washington Library Network) conspectus sheets, analysis of OCLC/AMIGOS Collection Analysis…

Using network analysis to study behavioural phenotypes: an example using domestic dogs.

PubMed

Goold, Conor; Vas, Judit; Olsen, Christine; Newberry, Ruth C

2016-10-01

Phenotypic integration describes the complex interrelationships between organismal traits, traditionally focusing on morphology. Recently, research has sought to represent behavioural phenotypes as composed of quasi-independent latent traits. Concurrently, psychologists have opposed latent variable interpretations of human behaviour, proposing instead a network perspective envisaging interrelationships between behaviours as emerging from causal dependencies. Network analysis could also be applied to understand integrated behavioural phenotypes in animals. Here, we assimilate this cross-disciplinary progression of ideas by demonstrating the use of network analysis on survey data collected on behavioural and motivational characteristics of police patrol and detection dogs ( Canis lupus familiaris ). Networks of conditional independence relationships illustrated a number of functional connections between descriptors, which varied between dog types. The most central descriptors denoted desirable characteristics in both patrol and detection dog networks, with 'Playful' being widely correlated and possessing mediating relationships between descriptors. Bootstrap analyses revealed the stability of network results. We discuss the results in relation to previous research on dog personality, and benefits of using network analysis to study behavioural phenotypes. We conclude that a network perspective offers widespread opportunities for advancing the understanding of phenotypic integration in animal behaviour.

Efficient Embedded Decoding of Neural Network Language Models in a Machine Translation System.

PubMed

Zamora-Martinez, Francisco; Castro-Bleda, Maria Jose

2018-02-22

Neural Network Language Models (NNLMs) are a successful approach to Natural Language Processing tasks, such as Machine Translation. We introduce in this work a Statistical Machine Translation (SMT) system which fully integrates NNLMs in the decoding stage, breaking the traditional approach based on [Formula: see text]-best list rescoring. The neural net models (both language models (LMs) and translation models) are fully coupled in the decoding stage, allowing to more strongly influence the translation quality. Computational issues were solved by using a novel idea based on memorization and smoothing of the softmax constants to avoid their computation, which introduces a trade-off between LM quality and computational cost. These ideas were studied in a machine translation task with different combinations of neural networks used both as translation models and as target LMs, comparing phrase-based and [Formula: see text]-gram-based systems, showing that the integrated approach seems more promising for [Formula: see text]-gram-based systems, even with nonfull-quality NNLMs.

Discovering the hidden sub-network component in a ranked list of genes or proteins derived from genomic experiments

PubMed Central

García-Alonso, Luz; Alonso, Roberto; Vidal, Enrique; Amadoz, Alicia; de María, Alejandro; Minguez, Pablo; Medina, Ignacio; Dopazo, Joaquín

2012-01-01

Genomic experiments (e.g. differential gene expression, single-nucleotide polymorphism association) typically produce ranked list of genes. We present a simple but powerful approach which uses protein–protein interaction data to detect sub-networks within such ranked lists of genes or proteins. We performed an exhaustive study of network parameters that allowed us concluding that the average number of components and the average number of nodes per component are the parameters that best discriminate between real and random networks. A novel aspect that increases the efficiency of this strategy in finding sub-networks is that, in addition to direct connections, also connections mediated by intermediate nodes are considered to build up the sub-networks. The possibility of using of such intermediate nodes makes this approach more robust to noise. It also overcomes some limitations intrinsic to experimental designs based on differential expression, in which some nodes are invariant across conditions. The proposed approach can also be used for candidate disease-gene prioritization. Here, we demonstrate the usefulness of the approach by means of several case examples that include a differential expression analysis in Fanconi Anemia, a genome-wide association study of bipolar disorder and a genome-scale study of essentiality in cancer genes. An efficient and easy-to-use web interface (available at http://www.babelomics.org) based on HTML5 technologies is also provided to run the algorithm and represent the network. PMID:22844098

Loss of integrity and atrophy in cingulate structural covariance networks in Parkinson's disease.

PubMed

de Schipper, Laura J; van der Grond, Jeroen; Marinus, Johan; Henselmans, Johanna M L; van Hilten, Jacobus J

2017-01-01

In Parkinson's disease (PD), the relation between cortical brain atrophy on MRI and clinical progression is not straightforward. Determination of changes in structural covariance networks - patterns of covariance in grey matter density - has shown to be a valuable technique to detect subtle grey matter variations. We evaluated how structural network integrity in PD is related to clinical data. 3 Tesla MRI was performed in 159 PD patients. We used nine standardized structural covariance networks identified in 370 healthy subjects as a template in the analysis of the PD data. Clinical assessment comprised motor features (Movement Disorder Society-Unified Parkinson's Disease Rating Scale; MDS-UPDRS motor scale) and predominantly non-dopaminergic features (SEverity of Non-dopaminergic Symptoms in Parkinson's Disease; SENS-PD scale: postural instability and gait difficulty, psychotic symptoms, excessive daytime sleepiness, autonomic dysfunction, cognitive impairment and depressive symptoms). Voxel-based analyses were performed within networks significantly associated with PD. The anterior and posterior cingulate network showed decreased integrity, associated with the SENS-PD score, p = 0.001 (β = - 0.265, η p 2  = 0.070) and p = 0.001 (β = - 0.264, η p 2  = 0.074), respectively. Of the components of the SENS-PD score, cognitive impairment and excessive daytime sleepiness were associated with atrophy within both networks. We identified loss of integrity and atrophy in the anterior and posterior cingulate networks in PD patients. Abnormalities of both networks were associated with predominantly non-dopaminergic features, specifically cognition and excessive daytime sleepiness. Our findings suggest that (components of) the cingulate networks display a specific vulnerability to the pathobiology of PD and may operate as interfaces between networks involved in cognition and alertness.

Discovery of Cellular Proteins Required for the Early Steps of HCV Infection Using Integrative Genomics

PubMed Central

Yang, Jae-Seong; Kwon, Oh Sung; Kim, Sanguk; Jang, Sung Key

2013-01-01

Successful viral infection requires intimate communication between virus and host cell, a process that absolutely requires various host proteins. However, current efforts to discover novel host proteins as therapeutic targets for viral infection are difficult. Here, we developed an integrative-genomics approach to predict human genes involved in the early steps of hepatitis C virus (HCV) infection. By integrating HCV and human protein associations, co-expression data, and tight junction-tetraspanin web specific networks, we identified host proteins required for the early steps in HCV infection. Moreover, we validated the roles of newly identified proteins in HCV infection by knocking down their expression using small interfering RNAs. Specifically, a novel host factor CD63 was shown to directly interact with HCV E2 protein. We further demonstrated that an antibody against CD63 blocked HCV infection, indicating that CD63 may serve as a new therapeutic target for HCV-related diseases. The candidate gene list provides a source for identification of new therapeutic targets. PMID:23593195

Performance Analysis of a NASA Integrated Network Array

NASA Technical Reports Server (NTRS)

Nessel, James A.

2012-01-01

The Space Communications and Navigation (SCaN) Program is planning to integrate its individual networks into a unified network which will function as a single entity to provide services to user missions. This integrated network architecture is expected to provide SCaN customers with the capabilities to seamlessly use any of the available SCaN assets to support their missions to efficiently meet the collective needs of Agency missions. One potential optimal application of these assets, based on this envisioned architecture, is that of arraying across existing networks to significantly enhance data rates and/or link availabilities. As such, this document provides an analysis of the transmit and receive performance of a proposed SCaN inter-network antenna array. From the study, it is determined that a fully integrated internetwork array does not provide any significant advantage over an intra-network array, one in which the assets of an individual network are arrayed for enhanced performance. Therefore, it is the recommendation of this study that NASA proceed with an arraying concept, with a fundamental focus on a network-centric arraying.

New Features in ADS Labs

NASA Astrophysics Data System (ADS)

Accomazzi, Alberto; Kurtz, M. J.; Henneken, E. A.; Grant, C. S.; Thompson, D.; Di Milia, G.; Luker, J.; Murray, S. S.

2013-01-01

The NASA Astrophysics Data System (ADS) has been working hard on updating its services and interfaces to better support our community's research needs. ADS Labs is a new interface built on the old tried-and-true ADS Abstract Databases, so all of ADS's content is available through it. In this presentation we highlight the new features that have been developed in ADS Labs over the last year: new recommendations, metrics, a citation tool and enhanced fulltext search. ADS Labs has long been providing article-level recommendations based on keyword similarity, co-readership and co-citation analysis of its corpus. We have now introduced personal recommendations, which provide a list of articles to be considered based on a individual user's readership history. A new metrics interface provides a summary of the basic impact indicators for a list of records. These include the total and normalized number of papers, citations, reads, and downloads. Also included are some of the popular indices such as the h, g and i10 index. The citation helper tool allows one to submit a set of records and obtain a list of top 10 papers which cite and/or are cited by papers in the original list (but which are not in it). The process closely resembles the network approach of establishing "friends of friends" via an analysis of the citation network. The full-text search service now covers more than 2.5 million documents, including all the major astronomy journals, as well as physics journals published by Springer, Elsevier, the American Physical Society, the American Geophysical Union, and all of the arXiv eprints. The full-text search interface interface allows users and librarians to dig deep and find words or phrases in the body of the indexed articles. ADS Labs is available at http://adslabs.org

Integrative network analysis unveils convergent molecular pathways in Parkinson's disease and diabetes.

PubMed

Santiago, Jose A; Potashkin, Judith A

2013-01-01

Shared dysregulated pathways may contribute to Parkinson's disease and type 2 diabetes, chronic diseases that afflict millions of people worldwide. Despite the evidence provided by epidemiological and gene profiling studies, the molecular and functional networks implicated in both diseases, have not been fully explored. In this study, we used an integrated network approach to investigate the extent to which Parkinson's disease and type 2 diabetes are linked at the molecular level. Using a random walk algorithm within the human functional linkage network we identified a molecular cluster of 478 neighboring genes closely associated with confirmed Parkinson's disease and type 2 diabetes genes. Biological and functional analysis identified the protein serine-threonine kinase activity, MAPK cascade, activation of the immune response, and insulin receptor and lipid signaling as convergent pathways. Integration of results from microarrays studies identified a blood signature comprising seven genes whose expression is dysregulated in Parkinson's disease and type 2 diabetes. Among this group of genes, is the amyloid precursor protein (APP), previously associated with neurodegeneration and insulin regulation. Quantification of RNA from whole blood of 192 samples from two independent clinical trials, the Harvard Biomarker Study (HBS) and the Prognostic Biomarker Study (PROBE), revealed that expression of APP is significantly upregulated in Parkinson's disease patients compared to healthy controls. Assessment of biomarker performance revealed that expression of APP could distinguish Parkinson's disease from healthy individuals with a diagnostic accuracy of 80% in both cohorts of patients. These results provide the first evidence that Parkinson's disease and diabetes are strongly linked at the molecular level and that shared molecular networks provide an additional source for identifying highly sensitive biomarkers. Further, these results suggest for the first time that increased expression of APP in blood may modulate the neurodegenerative phenotype in type 2 diabetes patients.

DELIVERing Library Resources to the Virtual Learning Environment

ERIC Educational Resources Information Center

Secker, Jane

2005-01-01

Purpose: Examines a project to integrate digital libraries and virtual learning environments (VLE) focusing on requirements for online reading list systems. Design/methodology/approach: Conducted a user needs analysis using interviews and focus groups and evaluated three reading or resource list management systems. Findings: Provides a technical…

Fostering Earth Observation Regional Networks - Integrative and iterative approaches to capacity building

NASA Astrophysics Data System (ADS)

Habtezion, S.

2015-12-01

Fostering Earth Observation Regional Networks - Integrative and iterative approaches to capacity building Fostering Earth Observation Regional Networks - Integrative and iterative approaches to capacity building Senay Habtezion (shabtezion@start.org) / Hassan Virji (hvirji@start.org)Global Change SySTem for Analysis, Training and Research (START) (www.start.org) 2000 Florida Avenue NW, Suite 200 Washington, DC 20009 USA As part of the Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) project partnership effort to promote use of earth observations in advancing scientific knowledge, START works to bridge capacity needs related to earth observations (EOs) and their applications in the developing world. GOFC-GOLD regional networks, fostered through the support of regional and thematic workshops, have been successful in (1) enabling participation of scientists for developing countries and from the US to collaborate on key GOFC-GOLD and Land Cover and Land Use Change (LCLUC) issues, including NASA Global Data Set validation and (2) training young developing country scientists to gain key skills in EOs data management and analysis. Members of the regional networks are also engaged and reengaged in other EOs programs (e.g. visiting scientists program; data initiative fellowship programs at the USGS EROS Center and Boston University), which has helped strengthen these networks. The presentation draws from these experiences in advocating for integrative and iterative approaches to capacity building through the lens of the GOFC-GOLD partnership effort. Specifically, this presentation describes the role of the GODC-GOLD partnership in nurturing organic networks of scientists and EOs practitioners in Asia, Africa, Eastern Europe and Latin America.

Six elements of integrated primary healthcare.

PubMed

Brown, Lynsey J; Oliver-Baxter, Jodie

2016-03-01

Integrated care has the potential to deliver efficiencies and improvements in patient experiences and health outcomes. Efforts towards integrated care, especially at the primary and community health levels, have increasingly been under focus, both nationally and internationally. In Australia, regional integration is a priority, and integration of care is a task for meso-level organisations such as Primary Health Networks (PHNs). This paper seeks to provide a list of elements and questions for consideration by organisations working across primary healthcare settings, looking to enact and improve the delivery of integrated care. Six elements that consistently emerged during the development of a series of rapid reviews on integrated primary healthcare in Australia are presented in this paper. The elements identified are context, governance and leadership, infrastructure, financing, engagement, and communication. They offer a starting point for reflection in the planning and practices of organisations in their drive for continuous improvements in integrated care.

Network propagation in the cytoscape cyberinfrastructure.

PubMed

Carlin, Daniel E; Demchak, Barry; Pratt, Dexter; Sage, Eric; Ideker, Trey

2017-10-01

Network propagation is an important and widely used algorithm in systems biology, with applications in protein function prediction, disease gene prioritization, and patient stratification. However, up to this point it has required significant expertise to run. Here we extend the popular network analysis program Cytoscape to perform network propagation as an integrated function. Such integration greatly increases the access to network propagation by putting it in the hands of biologists and linking it to the many other types of network analysis and visualization available through Cytoscape. We demonstrate the power and utility of the algorithm by identifying mutations conferring resistance to Vemurafenib.

Pathway-based variant enrichment analysis on the example of dilated cardiomyopathy.

PubMed

Backes, Christina; Meder, Benjamin; Lai, Alan; Stoll, Monika; Rühle, Frank; Katus, Hugo A; Keller, Andreas

2016-01-01

Genome-wide association (GWA) studies have significantly contributed to the understanding of human genetic variation and its impact on clinical traits. Frequently only a limited number of highly significant associations were considered as biologically relevant. Increasingly, network analysis of affected genes is used to explore the potential role of the genetic background on disease mechanisms. Instead of first determining affected genes or calculating scores for genes and performing pathway analysis on the gene level, we integrated both steps and directly calculated enrichment on the genetic variant level. The respective approach has been tested on dilated cardiomyopathy (DCM) GWA data as showcase. To compute significance values, 5000 permutation tests were carried out and p values were adjusted for multiple testing. For 282 KEGG pathways, we computed variant enrichment scores and significance values. Of these, 65 were significant. Surprisingly, we discovered the "nucleotide excision repair" and "tuberculosis" pathways to be most significantly associated with DCM (p = 10(-9)). The latter pathway is driven by genes of the HLA-D antigen group, a finding that closely resembles previous discoveries made by expression quantitative trait locus analysis in the context of DCM-GWA. Next, we implemented a sub-network-based analysis, which searches for affected parts of KEGG, however, independent on the pre-defined pathways. Here, proteins of the contractile apparatus of cardiac cells as well as the FAS sub-network were found to be affected by common polymorphisms in DCM. In this work, we performed enrichment analysis directly on variants, leveraging the potential to discover biological information in thousands of published GWA studies. The applied approach is cutoff free and considers a ranked list of genetic variants as input.

INTEGRATED ENVIRONMENTAL ASSESSMENT OF THE MID-ATLANTIC REGION WITH ANALYTICAL NETWORK PROCESS

EPA Science Inventory

A decision analysis method for integrating environmental indicators was developed. This was a combination of Principal Component Analysis (PCA) and the Analytic Network Process (ANP). Being able to take into account interdependency among variables, the method was capable of ran...

GARNET--gene set analysis with exploration of annotation relations.

PubMed

Rho, Kyoohyoung; Kim, Bumjin; Jang, Youngjun; Lee, Sanghyun; Bae, Taejeong; Seo, Jihae; Seo, Chaehwa; Lee, Jihyun; Kang, Hyunjung; Yu, Ungsik; Kim, Sunghoon; Lee, Sanghyuk; Kim, Wan Kyu

2011-02-15

Gene set analysis is a powerful method of deducing biological meaning for an a priori defined set of genes. Numerous tools have been developed to test statistical enrichment or depletion in specific pathways or gene ontology (GO) terms. Major difficulties towards biological interpretation are integrating diverse types of annotation categories and exploring the relationships between annotation terms of similar information. GARNET (Gene Annotation Relationship NEtwork Tools) is an integrative platform for gene set analysis with many novel features. It includes tools for retrieval of genes from annotation database, statistical analysis & visualization of annotation relationships, and managing gene sets. In an effort to allow access to a full spectrum of amassed biological knowledge, we have integrated a variety of annotation data that include the GO, domain, disease, drug, chromosomal location, and custom-defined annotations. Diverse types of molecular networks (pathways, transcription and microRNA regulations, protein-protein interaction) are also included. The pair-wise relationship between annotation gene sets was calculated using kappa statistics. GARNET consists of three modules--gene set manager, gene set analysis and gene set retrieval, which are tightly integrated to provide virtually automatic analysis for gene sets. A dedicated viewer for annotation network has been developed to facilitate exploration of the related annotations. GARNET (gene annotation relationship network tools) is an integrative platform for diverse types of gene set analysis, where complex relationships among gene annotations can be easily explored with an intuitive network visualization tool (http://garnet.isysbio.org/ or http://ercsb.ewha.ac.kr/garnet/).

Disrupted topology of the resting state structural connectome in middle-aged APOE ε4 carriers.

PubMed

Korthauer, L E; Zhan, L; Ajilore, O; Leow, A; Driscoll, I

2018-05-24

The apolipoprotein E (APOE) ε4 allele is the best characterized genetic risk factor for Alzheimer's disease to date. Older APOE ε4 carriers (aged 60 + years) are known to have disrupted structural and functional connectivity, but less is known about APOE-associated network integrity in middle age. The goal of this study was to characterize APOE-related differences in network topology in middle age, as disentangling the early effects of healthy versus pathological aging may aid early detection of Alzheimer's disease and inform treatments. We performed resting state functional magnetic resonance imaging (rs-fMRI) and diffusion tensor imaging (DTI) in healthy, cognitively normal, middle-aged adults (age 40-60; N = 76, 38 APOE ε4 carriers). Graph theoretical analysis was used to calculate local and global efficiency of 1) a whole brain rs-fMRI network; 2) a whole brain DTI network; and 3) the resting state structural connectome (rsSC), an integrated functional-structural network derived using functional-by-structural hierarchical (FSH) mapping. Our results indicated no APOE ε4-associated differences in network topology of the rs-fMRI or DTI networks alone. However, ε4 carriers had significantly lower global and local efficiency of the integrated rsSC compared to non-carriers. Furthermore, ε4 carriers were less resilient to targeted node failure of the rsSC, which mimics the neuropathological process of Alzheimer's disease. Collectively, these findings suggest that integrating multiple neuroimaging modalities and employing graph theoretical analysis may reveal network-level vulnerabilities that may serve as biomarkers of age-related cognitive decline in middle age, decades before the onset of overt cognitive impairment. Copyright © 2018. Published by Elsevier Inc.

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis

DOE PAGES

Pavlopoulos, Georgios A.; Paez-Espino, David; Kyrpides, Nikos C.; ...

2017-07-18

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses andmore » empirically discuss their scalability, user friendliness, and postvisualization capabilities.« less

Empirical Comparison of Visualization Tools for Larger-Scale Network Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pavlopoulos, Georgios A.; Paez-Espino, David; Kyrpides, Nikos C.

Gene expression, signal transduction, protein/chemical interactions, biomedical literature cooccurrences, and other concepts are often captured in biological network representations where nodes represent a certain bioentity and edges the connections between them. While many tools to manipulate, visualize, and interactively explore such networks already exist, only few of them can scale up and follow today’s indisputable information growth. In this review, we shortly list a catalog of available network visualization tools and, from a user-experience point of view, we identify four candidate tools suitable for larger-scale network analysis, visualization, and exploration. Lastly, we comment on their strengths and their weaknesses andmore » empirically discuss their scalability, user friendliness, and postvisualization capabilities.« less

Teaching bioinformatics and neuroinformatics by using free web-based tools.

PubMed

Grisham, William; Schottler, Natalie A; Valli-Marill, Joanne; Beck, Lisa; Beatty, Jackson

2010-01-01

This completely computer-based module's purpose is to introduce students to bioinformatics resources. We present an easy-to-adopt module that weaves together several important bioinformatic tools so students can grasp how these tools are used in answering research questions. Students integrate information gathered from websites dealing with anatomy (Mouse Brain Library), quantitative trait locus analysis (WebQTL from GeneNetwork), bioinformatics and gene expression analyses (University of California, Santa Cruz Genome Browser, National Center for Biotechnology Information's Entrez Gene, and the Allen Brain Atlas), and information resources (PubMed). Instructors can use these various websites in concert to teach genetics from the phenotypic level to the molecular level, aspects of neuroanatomy and histology, statistics, quantitative trait locus analysis, and molecular biology (including in situ hybridization and microarray analysis), and to introduce bioinformatic resources. Students use these resources to discover 1) the region(s) of chromosome(s) influencing the phenotypic trait, 2) a list of candidate genes-narrowed by expression data, 3) the in situ pattern of a given gene in the region of interest, 4) the nucleotide sequence of the candidate gene, and 5) articles describing the gene. Teaching materials such as a detailed student/instructor's manual, PowerPoints, sample exams, and links to free Web resources can be found at http://mdcune.psych.ucla.edu/modules/bioinformatics.

The evolution of social networks through the implementation of evidence-informed decision-making interventions: a longitudinal analysis of three public health units in Canada.

PubMed

Yousefi-Nooraie, Reza; Dobbins, Maureen; Marin, Alexandra; Hanneman, Robert; Lohfeld, Lynne

2015-12-03

We studied the evolution of information-seeking networks over a 2-year period during which an organization-wide intervention was implemented to promote evidence-informed decision-making (EIDM) in three public health units in Ontario, Canada. We tested whether engagement of staff in the intervention and their EIDM behavior were associated with being chosen as information source and how the trend of inter-divisional communications and the dominance of experts evolved over time. Local managers at each health unit selected a group of staff to get engage in Knowledge Broker-led workshops and development of evidence summaries to address local public health problems. The staff were invited to answer three online surveys (at baseline and two annual follow-ups) including name generator questions eliciting the list of the staff they would turn to for help integrating research evidence into practice. We used stochastic actor-oriented modeling to study the evolution of networks. We tested the effect of engagement in the intervention, EIDM behavior scores, organizational divisions, and structural dynamics of social networks on the tendency of staff to select information sources, and the change in its trend between year 1 and year 2 of follow-up. In all the three health units, and especially in the two units with higher levels of engagement in the intervention, the network evolved towards a more centralized structure, with an increasing significance of already central staff. The staff showed greater tendencies to seek information from peers with higher EIDM behavior scores. In the public health unit that had highest engagement and stronger leadership support, the engaged staff became more central. In all public health units, the engaged staff showed an increasing tendency towards forming clusters. The staff in the three public health units showed a tendency towards limiting their connections within their divisions. The longitudinal analysis provided us with a means to study the microstructural changes in public health units, clues to the sustainability of the implementation. The hierarchical transformation of networks towards experts and formation of clusters among staff who were engaged in the intervention show how implementing organizational interventions to promote EIDM may affect the knowledge flow and distribution in health care communities, which may lead to unanticipated consequences.

Analysis of the characteristics of the synchronous clusters in the adaptive Kuramoto network and neural network of the epileptic brain

NASA Astrophysics Data System (ADS)

Hramov, Alexander E.; Kharchenko, Alexander A.; Makarov, Vladimir V.; Khramova, Marina V.; Koronovskii, Alexey A.; Pavlov, Alexey N.; Dana, Syamal K.

2016-04-01

In the paper we study the mechanisms of phase synchronization in the adaptive model network of Kuramoto oscillators and the neural network of brain by consideration of the integral characteristics of the observed networks signals. As the integral characteristics of the model network we consider the summary signal produced by the oscillators. Similar to the model situation we study the ECoG signal as the integral characteristic of neural network of the brain. We show that the establishment of the phase synchronization results in the increase of the peak, corresponding to synchronized oscillators, on the wavelet energy spectrum of the integral signals. The observed correlation between the phase relations of the elements and the integral characteristics of the whole network open the way to detect the size of synchronous clusters in the neural networks of the epileptic brain before and during seizure.

Neural correlates of processing sentences and compound words in Chinese

PubMed Central

Hung, Yi-Hui; Tzeng, Ovid; Wu, Denise H.

2017-01-01

Sentence reading involves multiple linguistic operations including processing of lexical and compositional semantics, and determining structural and grammatical relationships among words. Previous studies on Indo-European languages have associated left anterior temporal lobe (aTL) and left interior frontal gyrus (IFG) with reading sentences compared to reading unstructured word lists. To examine whether these brain regions are also involved in reading a typologically distinct language with limited morphosyntax and lack of agreement between sentential arguments, an FMRI study was conducted to compare passive reading of Chinese sentences, unstructured word lists and disconnected character lists that are created by only changing the order of an identical set of characters. Similar to previous findings from other languages, stronger activation was found in mainly left-lateralized anterior temporal regions (including aTL) for reading sentences compared to unstructured word and character lists. On the other hand, stronger activation was identified in left posterior temporal sulcus for reading unstructured words compared to unstructured characters. Furthermore, reading unstructured word lists compared to sentences evoked stronger activation in left IFG and left inferior parietal lobule. Consistent with the literature on Indo-European languages, the present results suggest that left anterior temporal regions subserve sentence-level integration, while left IFG supports restoration of sentence structure. In addition, left posterior temporal sulcus is associated with morphological compounding. Taken together, reading Chinese sentences engages a common network as reading other languages, with particular reliance on integration of semantic constituents. PMID:29194453

Method and system for conserving power in a telecommunications network during emergency situations

DOEpatents

Conrad, Stephen H [Algodones, NM; O'Reilly, Gerard P [Manalapan, NJ

2011-10-11

Disclosed is a method and apparatus for conserving power in a telecommunications network during emergency situations. A permissible number list of emergency and/or priority numbers is stored in the telecommunications network. In the event of an emergency or power failure, input digits of a call to the telecommunications network are compared to the permissible number list. The call is processed in the telecommunications network and routed to its destination if the input digits match an entry in the permissible number list. The call is dropped without any further processing if the input digits do not match an entry in the permissible number list. Thus, power can be conserved in emergency situations by only allowing emergency and/or priority calls.

Seismic aftershock monitoring for on-site inspection purposes. Experience from Integrated Field Exercise 2008.

NASA Astrophysics Data System (ADS)

Labak, P.; Arndt, R.; Villagran, M.

2009-04-01

One of the sub-goals of the Integrated Field Experiment in 2008 (IFE08) in Kazakhstan was testing the prototype elements of the Seismic aftershock monitoring system (SAMS) for on-site inspection purposes. The task of the SAMS is to collect the facts, which should help to clarify nature of the triggering event. Therefore the SAMS has to be capable to detect and identify events as small as magnitude -2 in the inspection area size up to 1000 km2. Equipment for 30 mini-arrays and 10 3-component stations represented the field equipment of the SAMS. Each mini-array consisted of a central 3-component seismometer and 3 vertical seismometers at the distance about 100 m from the central seismometer. The mini-arrays covered approximately 80% of surrogate inspection area (IA) on the territory of former Semipalatinsk test site. Most of the stations were installed during the first four days of field operations by the seismic sub-team, which consisted of 10 seismologists. SAMS data center comprised 2 IBM Blade centers and 8 working places for data archiving, detection list production and event analysis. A prototype of SAMS software was tested. Average daily amount of collected raw data was 15-30 GB and increased according to the amount of stations entering operation. Routine manual data screening and data analyses were performed by 2-6 subteam members. Automatic screening was used for selected time intervals. Screening was performed using the Sonoview program in frequency domain and using the Geotool and Hypolines programs for screening in time domain. The screening results were merged into the master event list. The master event list served as a basis of detailed analysis of unclear events and events identified to be potentially in the IA. Detailed analysis of events to be potentially in the IA was performed by the Hypoline and Geotool programs. In addition, the Hyposimplex and Hypocenter programs were also used for localization of events. The results of analysis were integrated in the visual form using the Seistrain/geosearch program. Data were fully screened for the period 5.-13.9.2008. 360 teleseismic, regional and local events were identified. Results of the detection and analysis will be presented and consequences for further SAMS development will be discussed.

Integrating fragmented evidence by network meta-analysis: relative effectiveness of psychological interventions for adults with post-traumatic stress disorder.

PubMed

Gerger, H; Munder, T; Gemperli, A; Nüesch, E; Trelle, S; Jüni, P; Barth, J

2014-11-01

To summarize the available evidence on the effectiveness of psychological interventions for patients with post-traumatic stress disorder (PTSD). We searched bibliographic databases and reference lists of relevant systematic reviews and meta-analyses for randomized controlled trials that compared specific psychological interventions for adults with PTSD symptoms either head-to-head or against control interventions using non-specific intervention components, or against wait-list control. Two investigators independently extracted the data and assessed trial characteristics. The analyses included 4190 patients in 66 trials. An initial network meta-analysis showed large effect sizes (ESs) for all specific psychological interventions (ESs between -1.10 and -1.37) and moderate effects of psychological interventions that were used to control for non-specific intervention effects (ESs -0.58 and -0.62). ES differences between various types of specific psychological interventions were absent to small (ES differences between 0.00 and 0.27). Considerable between-trial heterogeneity occurred (τ²= 0.30). Stratified analyses revealed that trials that adhered to DSM-III/IV criteria for PTSD were associated with larger ESs. However, considerable heterogeneity remained. Heterogeneity was reduced in trials with adequate concealment of allocation and in large-sized trials. We found evidence for small-study bias. Our findings show that patients with a formal diagnosis of PTSD and those with subclinical PTSD symptoms benefit from different psychological interventions. We did not identify any intervention that was consistently superior to other specific psychological interventions. However, the robustness of evidence varies considerably between different psychological interventions for PTSD, with most robust evidence for cognitive behavioral and exposure therapies.

Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool

PubMed Central

2013-01-01

Background System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Results Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Conclusions Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr. PMID:23586463

Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool.

PubMed

Chen, Edward Y; Tan, Christopher M; Kou, Yan; Duan, Qiaonan; Wang, Zichen; Meirelles, Gabriela Vaz; Clark, Neil R; Ma'ayan, Avi

2013-04-15

System-wide profiling of genes and proteins in mammalian cells produce lists of differentially expressed genes/proteins that need to be further analyzed for their collective functions in order to extract new knowledge. Once unbiased lists of genes or proteins are generated from such experiments, these lists are used as input for computing enrichment with existing lists created from prior knowledge organized into gene-set libraries. While many enrichment analysis tools and gene-set libraries databases have been developed, there is still room for improvement. Here, we present Enrichr, an integrative web-based and mobile software application that includes new gene-set libraries, an alternative approach to rank enriched terms, and various interactive visualization approaches to display enrichment results using the JavaScript library, Data Driven Documents (D3). The software can also be embedded into any tool that performs gene list analysis. We applied Enrichr to analyze nine cancer cell lines by comparing their enrichment signatures to the enrichment signatures of matched normal tissues. We observed a common pattern of up regulation of the polycomb group PRC2 and enrichment for the histone mark H3K27me3 in many cancer cell lines, as well as alterations in Toll-like receptor and interlukin signaling in K562 cells when compared with normal myeloid CD33+ cells. Such analyses provide global visualization of critical differences between normal tissues and cancer cell lines but can be applied to many other scenarios. Enrichr is an easy to use intuitive enrichment analysis web-based tool providing various types of visualization summaries of collective functions of gene lists. Enrichr is open source and freely available online at: http://amp.pharm.mssm.edu/Enrichr.

Altered functional and effective connectivity in anticorrelated intrinsic networks in children with benign childhood epilepsy with centrotemporal spikes.

PubMed

Luo, Cheng; Yang, Fei; Deng, Jiayan; Zhang, Yaodan; Hou, Changyue; Huang, Yue; Cao, Weifang; Wang, Jianjun; Xiao, Ruhui; Zeng, Nanlin; Wang, Xiaoming; Yao, Dezhong

2016-06-01

There are 2 intrinsic networks in the human brain: the task positive network (TPN) and task negative network (alternately termed the default mode network, DMN) in which inverse correlations have been observed during resting state and event-related functional magnetic resonance imaging (fMRI). The antagonism between the 2 networks might indicate a dynamic interaction in the brain that is associated with development.To evaluate the alterations in the relations of the 2 networks in children with benign childhood epilepsy with centrotemporal spikes (BECTS), resting state fMRI was performed in 17 patients with BECTS and 17 healthy controls. The functional and effective connectivities of 29 nodes in the TPN and DMN were analyzed. Positive functional connectivity (FC) within the networks and negative FC between the 2 networks were observed in both groups.The patients exhibited increased FC within both networks, particularly in the frontoparietal nodes such as the left superior frontal cortex, and enhanced antagonism between the 2 networks, suggesting abnormal functional integration of the nodes of the 2 networks in the patients. Granger causality analysis revealed a significant difference in the degree of outflow to inflow in the left superior frontal cortex and the left ventral occipital lobe.The alterations observed in the combined functional and effective connectivity analyses might indicate an association of an abnormal ability to integrate information between the DMN and TPN and the epileptic neuropathology of BECTS and provide preliminary evidence supporting the occurrence of abnormal development in children with BECTS.

Basic Lessons in ORA and AutoMap 2012

DTIC Science & Technology

2012-06-11

boy named Dave. He has 2 balls. 1 ball is red. 1 ball is blue. milkAndCookies.txt: Dave wants milk and cookies. He drives to the store. He then buys... milk and cookies. 2. Create Concept List From the Pull Down Menu select Generate => Concept List => Concept List (per text). Navigate to where you...the thesaurus. Using the ThesauriContentOnly option You create a Meta-Network (Carley, 200) with the one-grams dog, cow , and farm. If you are going

New strategy for drug discovery by large-scale association analysis of molecular networks of different species.

PubMed

Zhang, Bo; Fu, Yingxue; Huang, Chao; Zheng, Chunli; Wu, Ziyin; Zhang, Wenjuan; Yang, Xiaoyan; Gong, Fukai; Li, Yuerong; Chen, Xiaoyu; Gao, Shuo; Chen, Xuetong; Li, Yan; Lu, Aiping; Wang, Yonghua

2016-02-25

The development of modern omics technology has not significantly improved the efficiency of drug development. Rather precise and targeted drug discovery remains unsolved. Here a large-scale cross-species molecular network association (CSMNA) approach for targeted drug screening from natural sources is presented. The algorithm integrates molecular network omics data from humans and 267 plants and microbes, establishing the biological relationships between them and extracting evolutionarily convergent chemicals. This technique allows the researcher to assess targeted drugs for specific human diseases based on specific plant or microbe pathways. In a perspective validation, connections between the plant Halliwell-Asada (HA) cycle and the human Nrf2-ARE pathway were verified and the manner by which the HA cycle molecules act on the human Nrf2-ARE pathway as antioxidants was determined. This shows the potential applicability of this approach in drug discovery. The current method integrates disparate evolutionary species into chemico-biologically coherent circuits, suggesting a new cross-species omics analysis strategy for rational drug development.

Modular thought in the circuit analysis

NASA Astrophysics Data System (ADS)

Wang, Feng

2018-04-01

Applied to solve the problem of modular thought, provides a whole for simplification's method, the complex problems have become of, and the study of circuit is similar to the above problems: the complex connection between components, make the whole circuit topic solution seems to be more complex, and actually components the connection between the have rules to follow, this article mainly tells the story of study on the application of the circuit modular thought. First of all, this paper introduces the definition of two-terminal network and the concept of two-terminal network equivalent conversion, then summarizes the common source resistance hybrid network modular approach, containing controlled source network modular processing method, lists the common module, typical examples analysis.

Integrating P3 Data Into P2 Analyses: What is the Added Value

Treesearch

James R. Steinman

2001-01-01

The Forest Inventory and Analysis and Forest Health Monitoring Programs of the USDA Forest Service are integrating field procedures for measuring their networks of plots throughout the United States. These plots are now referred to as Phase 2 (P2) and Phase 3 (P3) plots, respectively, and 1 out of every 16 P2 plots will also be a P3 plot. Mensurational methods will be...

14 CFR 249.2 - Definitions.

Code of Federal Regulations, 2014 CFR

2014-01-01

... constitute integral links in developing the history of, or facts regarding, financial transactions or... listings punched cards, computer-produced listings, microfilm, and magnetic storage media (i.e., magnetic...

14 CFR 249.2 - Definitions.

Code of Federal Regulations, 2013 CFR

2013-01-01

... constitute integral links in developing the history of, or facts regarding, financial transactions or... listings punched cards, computer-produced listings, microfilm, and magnetic storage media (i.e., magnetic...

14 CFR 249.2 - Definitions.

Code of Federal Regulations, 2012 CFR

2012-01-01

... constitute integral links in developing the history of, or facts regarding, financial transactions or... listings punched cards, computer-produced listings, microfilm, and magnetic storage media (i.e., magnetic...

14 CFR 249.2 - Definitions.

Code of Federal Regulations, 2011 CFR

2011-01-01

... constitute integral links in developing the history of, or facts regarding, financial transactions or... listings punched cards, computer-produced listings, microfilm, and magnetic storage media (i.e., magnetic...

The Potential Impact of a "No-Buy" List on Youth Exposure to Alcohol Advertising on Cable Television.

PubMed

Ross, Craig S; Brewer, Robert D; Jernigan, David H

2016-01-01

The purpose of this study was to outline a method to improve alcohol industry compliance with its self-regulatory advertising placement guidelines on television with the goal of reducing youth exposure to noncompliant advertisements. Data were sourced from Nielsen (The Nielsen Company, New York, NY) for all alcohol advertisements on television in the United States for 2005-2012. A "no-buy" list, that is a list of cable television programs and networks to be avoided when purchasing alcohol advertising, was devised using three criteria: avoid placements on programs that were noncompliant in the past (serially noncompliant), avoid placements on networks at times of day when youth make up a high proportion of the audience (high-risk network dayparts), and use a "guardbanded" (or more restrictive) composition guideline when placing ads on low-rated programs (low rated). Youth were exposed to 15.1 billion noncompliant advertising impressions from 2005 to 2012, mostly on cable television. Together, the three no-buy list criteria accounted for 99% of 12.9 billion noncompliant advertising exposures on cable television for youth ages 2-20 years. When we evaluated the no-buy list criteria sequentially and mutually exclusively, serially noncompliant ads accounted for 67% of noncompliant exposure, high-risk network-daypart ads accounted for 26%, and low-rated ads accounted for 7%. These findings suggest that the prospective use of the no-buy list criteria when purchasing alcohol advertising could eliminate most noncompliant advertising exposures and could be incorporated into standard post-audit procedures that are widely used by the alcohol industry in assessing exposure to television advertising.

High-Bandwidth Tactical-Network Data Analysis in a High-Performance-Computing (HPC) Environment: Device Status Data

DTIC Science & Technology

2015-09-01

Figures iv List of Tables iv 1. Introduction 1 2. Device Status Data 1 2.1 SNMP 1 2.2 NMS 1 2.3 ICMP Ping 2 3. Data Collection 2 4. Hydra ...Configuration 3 4.1 Status Codes 4 4.2 Request Time 5 4.3 Hydra BLOb Metadata 6 5. Data Processing 6 5.1 Hydra Data Processing Framework 6 5.1.1...Basic Components 6 5.1.2 Map Component 7 5.1.3 Postmap Methods 8 5.1.4 Data Flow 9 5.1.5 Distributed Processing Considerations 9 5.2 Specific Hydra

Performance Analysis of Hierarchical Group Key Management Integrated with Adaptive Intrusion Detection in Mobile ad hoc Networks

DTIC Science & Technology

2016-04-05

applications in wireless networks such as military battlefields, emergency response, mobile commerce , online gaming, and collaborative work are based on the...www.elsevier.com/locate/peva Performance analysis of hierarchical group key management integrated with adaptive intrusion detection in mobile ad hoc...Accepted 19 September 2010 Available online 26 September 2010 Keywords: Mobile ad hoc networks Intrusion detection Group communication systems Group

An option for measuring maternal mortality in developing countries: a survey using community informants.

PubMed

Qomariyah, Siti Nurul; Braunholtz, David; Achadi, Endang L; Witten, Karen H; Pambudi, Eko Setyo; Anggondowati, Trisari; Latief, Kamaluddin; Graham, Wendy J

2010-11-17

The maternal mortality ratio (MMR) remains high in most developing countries. Local, recent estimates of MMR are needed to motivate policymakers and evaluate interventions. But, estimating MMR, in the absence of vital registration systems, is difficult. This paper describes an efficient approach using village informant networks to capture maternal death cases (Maternal Deaths from Informants/Maternal Death Follow on Review or MADE-IN/MADE-FOR) developed to address this gap, and examines its validity and efficiency. MADE-IN used two village informant networks - heads of neighbourhood units (RTs) and health volunteers (Kaders). Informants were invited to attend separate network meetings - through the village head (for the RT) and through health centre for the kaders. Attached to the letter was a form with written instructions requesting informants list deaths of women of reproductive age (WRA) in the village during the previous two years. At a 'listing meeting' the informants' understanding on the form was checked, informants could correct their forms, and then collectively agreed a consolidated list. MADE-FOR consisted of visits relatives of likely pregnancy related deaths (PRDs) identified from MADE-IN, to confirm the PRD status and gather information about the cause of death. Capture-recapture (CRC) analysis enabled estimation of coverage rates of the two networks, and of total PRDs. The RT network identified a higher proportion of PRDs than the kaders (estimated 0.85 vs. 0.71), but the latter was easier and cheaper to access. Assigned PRD status amongst identified WRA deaths was more accurate for the kader network, and seemingly for more recent deaths, and for deaths from rural areas. Assuming information on live births from an existing source to calculate the MMR, MADE-IN/MADE-FOR cost only $0.1 (US) per women-year risk of exposure, substantially cheaper than alternatives. This study shows that reliable local, recent estimates of MMR can be obtained relatively cheaply using two independent informant networks to identify cases. Neither network captured all PRDs, but capture-recapture analysis allowed self-calibration. However, it requires careful avoidance of false-positives, and matching of cases identified by both networks, which was achieved by the home visit.

Nuclear Data Needs for the Neutronic Design of MYRRHA Fast Spectrum Research Reactor

NASA Astrophysics Data System (ADS)

Stankovskiy, A.; Malambu, E.; Van den Eynde, G.; Díez, C. J.

2014-04-01

A global sensitivity analysis of effective neutron multiplication factor to the change of nuclear data library has been performed. It revealed that the test version of JEFF-3.2 neutron-induced evaluated data library produces closer results to ENDF/B-VII.1 than JEFF-3.1.2 does. The analysis of contributions of individual evaluations into keff sensitivity resulted in the priority list of nuclides, uncertainties on cross sections and fission neutron multiplicities of which have to be improved by setting up dedicated differential and integral experiments.

An integrated systems genetics screen reveals the transcriptional structure of inherited predisposition to metastatic disease

PubMed Central

Faraji, Farhoud; Hu, Ying; Wu, Gang; Goldberger, Natalie E.; Walker, Renard C.; Zhang, Jinghui; Hunter, Kent W.

2014-01-01

Metastasis is the result of stochastic genomic and epigenetic events leading to gene expression profiles that drive tumor dissemination. Here we exploit the principle that metastatic propensity is modified by the genetic background to generate prognostic gene expression signatures that illuminate regulators of metastasis. We also identify multiple microRNAs whose germline variation is causally linked to tumor progression and metastasis. We employ network analysis of global gene expression profiles in tumors derived from a panel of recombinant inbred mice to identify a network of co-expressed genes centered on Cnot2 that predicts metastasis-free survival. Modulating Cnot2 expression changes tumor cell metastatic potential in vivo, supporting a functional role for Cnot2 in metastasis. Small RNA sequencing of the same tumor set revealed a negative correlation between expression of the Mir216/217 cluster and tumor progression. Expression quantitative trait locus analysis (eQTL) identified cis-eQTLs at the Mir216/217 locus, indicating that differences in expression may be inherited. Ectopic expression of Mir216/217 in tumor cells suppressed metastasis in vivo. Finally, small RNA sequencing and mRNA expression profiling data were integrated to reveal that miR-3470a/b target a high proportion of network transcripts. In vivo analysis of Mir3470a/b demonstrated that both promote metastasis. Moreover, Mir3470b is a likely regulator of the Cnot2 network as its overexpression down-regulated expression of network hub genes and enhanced metastasis in vivo, phenocopying Cnot2 knockdown. The resulting data from this strategy identify Cnot2 as a novel regulator of metastasis and demonstrate the power of our systems-level approach in identifying modifiers of metastasis. PMID:24322557

Crew Integration & Automation Testbed and Robotic Follower Programs

DTIC Science & Technology

2001-05-30

Evolving Technologies for Reduced Crew Operation” Vehicle Tech Demo #1 (VTT) Vehicle Tech Demo #2 ( CAT ATD) Two Man Transition Future Combat...Simulation Advanced Electronic Architecture Concept Vehicle Shown with Onboard Safety Driver Advanced Interfaces CAT ATD Exit Criteria...Provide 1000 Hz control loop for critical real-time tasks CAT Workload IPT Process and Product Schedule Crew Task List Task Timelines Workload Analysis

Optimal Network for Patients with Severe Mental Illness: A Social Network Analysis.

PubMed

Lorant, Vincent; Nazroo, James; Nicaise, Pablo

2017-11-01

It is still unclear what the optimal structure of mental health care networks should be. We examine whether certain types of network structure have been associated with improved continuity of care and greater social integration. A social network survey was carried out, covering 954 patients across 19 mental health networks in Belgium in 2014. We found continuity of care to be associated with large, centralized, and homophilous networks, whereas social integration was associated with smaller, centralized, and heterophilous networks. Two important goals of mental health service provision, continuity of care and social integration, are associated with different types of network. Further research is needed to ascertain the direction of this association.

Integrative Analysis Reveals Regulatory Programs in Endometriosis

PubMed Central

Yang, Huan; Kang, Kai; Cheng, Chao; Mamillapalli, Ramanaiah; Taylor, Hugh S.

2015-01-01

Endometriosis is a common gynecological disease found in approximately 10% of reproductive-age women. Gene expression analysis has been performed to explore alterations in gene expression associated with endometriosis; however, the underlying transcription factors (TFs) governing such expression changes have not been investigated in a systematic way. In this study, we propose a method to integrate gene expression with TF binding data and protein–protein interactions to construct an integrated regulatory network (IRN) for endometriosis. The IRN has shown that the most regulated gene in endometriosis is RUNX1, which is targeted by 14 of 26 TFs also involved in endometriosis. Using 2 published cohorts, GSE7305 (Hover, n = 20) and GSE7307 (Roth, n = 36) from the Gene Expression Omnibus database, we identified a network of TFs, which bind to target genes that are differentially expressed in endometriosis. Enrichment analysis based on the hypergeometric distribution allowed us to predict the TFs involved in endometriosis (n = 40). This included known TFs such as androgen receptor (AR) and critical factors in the pathology of endometriosis, estrogen receptor α, and estrogen receptor β. We also identified several new ones from which we selected FOXA2 and TFAP2C, and their regulation was confirmed by quantitative real-time polymerase chain reaction and immunohistochemistry (IHC). Further, our analysis revealed that the function of AR and p53 in endometriosis is regulated by posttranscriptional changes and not by differential gene expression. Our integrative analysis provides new insights into the regulatory programs involved in endometriosis. PMID:26134036

Multisensory integration processing during olfactory-visual stimulation-An fMRI graph theoretical network analysis.

PubMed

Ripp, Isabelle; Zur Nieden, Anna-Nora; Blankenagel, Sonja; Franzmeier, Nicolai; Lundström, Johan N; Freiherr, Jessica

2018-05-07

In this study, we aimed to understand how whole-brain neural networks compute sensory information integration based on the olfactory and visual system. Task-related functional magnetic resonance imaging (fMRI) data was obtained during unimodal and bimodal sensory stimulation. Based on the identification of multisensory integration processing (MIP) specific hub-like network nodes analyzed with network-based statistics using region-of-interest based connectivity matrices, we conclude the following brain areas to be important for processing the presented bimodal sensory information: right precuneus connected contralaterally to the supramarginal gyrus for memory-related imagery and phonology retrieval, and the left middle occipital gyrus connected ipsilaterally to the inferior frontal gyrus via the inferior fronto-occipital fasciculus including functional aspects of working memory. Applied graph theory for quantification of the resulting complex network topologies indicates a significantly increased global efficiency and clustering coefficient in networks including aspects of MIP reflecting a simultaneous better integration and segregation. Graph theoretical analysis of positive and negative network correlations allowing for inferences about excitatory and inhibitory network architectures revealed-not significant, but very consistent-that MIP-specific neural networks are dominated by inhibitory relationships between brain regions involved in stimulus processing. © 2018 Wiley Periodicals, Inc.

An extensive analysis of disease-gene associations using network integration and fast kernel-based gene prioritization methods.

PubMed

Valentini, Giorgio; Paccanaro, Alberto; Caniza, Horacio; Romero, Alfonso E; Re, Matteo

2014-06-01

In the context of "network medicine", gene prioritization methods represent one of the main tools to discover candidate disease genes by exploiting the large amount of data covering different types of functional relationships between genes. Several works proposed to integrate multiple sources of data to improve disease gene prioritization, but to our knowledge no systematic studies focused on the quantitative evaluation of the impact of network integration on gene prioritization. In this paper, we aim at providing an extensive analysis of gene-disease associations not limited to genetic disorders, and a systematic comparison of different network integration methods for gene prioritization. We collected nine different functional networks representing different functional relationships between genes, and we combined them through both unweighted and weighted network integration methods. We then prioritized genes with respect to each of the considered 708 medical subject headings (MeSH) diseases by applying classical guilt-by-association, random walk and random walk with restart algorithms, and the recently proposed kernelized score functions. The results obtained with classical random walk algorithms and the best single network achieved an average area under the curve (AUC) across the 708 MeSH diseases of about 0.82, while kernelized score functions and network integration boosted the average AUC to about 0.89. Weighted integration, by exploiting the different "informativeness" embedded in different functional networks, outperforms unweighted integration at 0.01 significance level, according to the Wilcoxon signed rank sum test. For each MeSH disease we provide the top-ranked unannotated candidate genes, available for further bio-medical investigation. Network integration is necessary to boost the performances of gene prioritization methods. Moreover the methods based on kernelized score functions can further enhance disease gene ranking results, by adopting both local and global learning strategies, able to exploit the overall topology of the network. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Exe-Guard Project

DOE Office of Scientific and Technical Information (OSTI.GOV)

Smith, Rhett; Marshall, Tim; Chavez, Adrian

The exe-Guard Project is an alliance between Dominion Virginia Power (DVP), Sandia National Laboratories (SNL), Dartmouth University, and Schweitzer Engineering Laboratories (SEL). SEL is primary recipient on this project. The exe-Guard project was selected for award under DE-FOA-0000359 with CFDA number 81.122 to address Topic Area of Interest 4: Hardened platforms and Systems. The exe-Guard project developed an antivirus solution for control system embedded devices to prevent the execution of unauthorized code and maintain settings and configuration integrity. This project created a white list antivirus solution for control systems capable of running on embedded Linux® operating systems. White list antivirusmore » methods allow only credible programs to run through the use of digital signatures and hash functions. Once a system’s secure state is baselined, white list antivirus software denies deviations from that state because of the installation of malicious code as this changes hash results. Black list antivirus software has been effective in traditional IT environments but has negative implications for control systems. Black list antivirus uses pattern matching and behavioral analysis to identify system threats while relying on regular updates to the signature file and recurrent system scanning. Black list antivirus is vulnerable to zero day exploits which have not yet been incorporated into a signature file update. System scans hamper the performance of high availability applications, as revealed in NIST special publication 1058 which summarizes the impact of blacklist antivirus on control systems: Manual or “on-demand” scanning has a major effect on control processes in that they take CPU time needed by the control process (Sometimes close to 100% of CPU time). Minimizing the antivirus software throttle setting will reduce but not eliminate this effect. Signature updates can also take up to 100% of CPU time, but for a much shorter period than a typical manual scanning process. Control systems are vulnerable to performance losses if off-the-shelf blacklist antivirus solutions aren’t implemented with care. This investment in configuration in addition to constant decommissioning to perform manual signature file updates is unprecedented and impractical. Additionally, control systems are often disconnected or islanded from the network making the delivery of signature updates difficult. Exe-Guard project developed a white list antivirus solution that mitigated the above drawbacks and allows control systems to cost-effectively apply malware protection while maintaining high reliability. The application of security patches can also be minimized since white listing maintains constant defense against unauthorized code execution. Security patches can instead be applied in less frequent intervals where system decommissioning can be scheduled and planned for. Since control systems are less dynamic than IT environments, the feasibility of maintaining a secure baselined state is more practical. Because upgrades are performed in infrequent, calculated intervals, it allows a new security baseline to be established before the system is returned to service. Exe-Guard built on the efforts of SNL under the Code Seal project. SNL demonstrated prototype Trust Anchors on the project which are independent monitoring and control devices that can be integrated into untrustworthy components. The exe-Guard team started with the lessons learned under this project then designed commercial solution for white list malware protection. Malware is a real threat, even on islanded or un-networked installations, since operators can unintentionally install infected files, plug in infected mass storage devices, or infect a piece of equipment on the islanded local area network that can then spread to other connected equipment. Protection at the device level is one of the last layers of defense in a security-in-depth defense model before an asset becomes compromised. This project provided non-destructive intrusion, isolation and automated response solution, achieving a goal of the Department of Energy (DOE) Roadmap to Secure Control Systems. It also addressed CIP-007-R4 which requires asset owners to employ malicious software prevention tools on assets within the electronic security perimeter. In addition, the CIP-007-R3 requirement for security patch management is minimized because white listing narrows the impact of vulnerabilities and patch releases. The exe-Guard Project completed all tasks identified in the statement of project objective and identified additional tasks within scope that were performed and completed within the original budget. The cost share was met and all deliverables were successfully completed and submitted on time. Most importantly the technology developed and commercialized under this project has been adopted by the Energy sector and thousands of devices with exe-Guard technology integrated in them have now been deployed and are protecting our power systems today« less

Large-scale integrative network-based analysis identifies common pathways disrupted by copy number alterations across cancers

PubMed Central

2013-01-01

Background Many large-scale studies analyzed high-throughput genomic data to identify altered pathways essential to the development and progression of specific types of cancer. However, no previous study has been extended to provide a comprehensive analysis of pathways disrupted by copy number alterations across different human cancers. Towards this goal, we propose a network-based method to integrate copy number alteration data with human protein-protein interaction networks and pathway databases to identify pathways that are commonly disrupted in many different types of cancer. Results We applied our approach to a data set of 2,172 cancer patients across 16 different types of cancers, and discovered a set of commonly disrupted pathways, which are likely essential for tumor formation in majority of the cancers. We also identified pathways that are only disrupted in specific cancer types, providing molecular markers for different human cancers. Analysis with independent microarray gene expression datasets confirms that the commonly disrupted pathways can be used to identify patient subgroups with significantly different survival outcomes. We also provide a network view of disrupted pathways to explain how copy number alterations affect pathways that regulate cell growth, cycle, and differentiation for tumorigenesis. Conclusions In this work, we demonstrated that the network-based integrative analysis can help to identify pathways disrupted by copy number alterations across 16 types of human cancers, which are not readily identifiable by conventional overrepresentation-based and other pathway-based methods. All the results and source code are available at http://compbio.cs.umn.edu/NetPathID/. PMID:23822816

Integrated Systems Biology Analysis of Transcriptomes Reveals Candidate Genes for Acidity Control in Developing Fruits of Sweet Orange (Citrus sinensis L. Osbeck).

PubMed

Huang, Dingquan; Zhao, Yihong; Cao, Minghao; Qiao, Liang; Zheng, Zhi-Liang

2016-01-01

Organic acids, such as citrate and malate, are important contributors for the sensory traits of fleshy fruits. Although their biosynthesis has been illustrated, regulatory mechanisms of acid accumulation remain to be dissected. To provide transcriptional architecture and identify candidate genes for citrate accumulation in fruits, we have selected for transcriptome analysis four varieties of sweet orange (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). Fruits of these varieties at 45 days post anthesis (DPA), which corresponds to Stage I (cell division), had similar acidity, but they displayed differential acid accumulation at 142 DPA (Stage II, cell expansion). Transcriptomes of fruits at 45 and 142 DPA were profiled using RNA sequencing and analyzed with three different algorithms (Pearson correlation, gene coexpression network and surrogate variable analysis). Our network analysis shows that the acid-correlated genes belong to three distinct network modules. Several of these candidate fruit acidity genes encode regulatory proteins involved in transport (such as AHA10), degradation (such as APD2) and transcription (such as AIL6) and act as hubs in the citrate accumulation gene networks. Taken together, our integrated systems biology analysis has provided new insights into the fruit citrate accumulation gene network and led to the identification of candidate genes likely associated with the fruit acidity control.

Integrated Systems Biology Analysis of Transcriptomes Reveals Candidate Genes for Acidity Control in Developing Fruits of Sweet Orange (Citrus sinensis L. Osbeck)

PubMed Central

Huang, Dingquan; Zhao, Yihong; Cao, Minghao; Qiao, Liang; Zheng, Zhi-Liang

2016-01-01

Organic acids, such as citrate and malate, are important contributors for the sensory traits of fleshy fruits. Although their biosynthesis has been illustrated, regulatory mechanisms of acid accumulation remain to be dissected. To provide transcriptional architecture and identify candidate genes for citrate accumulation in fruits, we have selected for transcriptome analysis four varieties of sweet orange (Citrus sinensis L. Osbeck) with varying fruit acidity, Succari (acidless), Bingtang (low acid), and Newhall and Xinhui (normal acid). Fruits of these varieties at 45 days post anthesis (DPA), which corresponds to Stage I (cell division), had similar acidity, but they displayed differential acid accumulation at 142 DPA (Stage II, cell expansion). Transcriptomes of fruits at 45 and 142 DPA were profiled using RNA sequencing and analyzed with three different algorithms (Pearson correlation, gene coexpression network and surrogate variable analysis). Our network analysis shows that the acid-correlated genes belong to three distinct network modules. Several of these candidate fruit acidity genes encode regulatory proteins involved in transport (such as AHA10), degradation (such as APD2) and transcription (such as AIL6) and act as hubs in the citrate accumulation gene networks. Taken together, our integrated systems biology analysis has provided new insights into the fruit citrate accumulation gene network and led to the identification of candidate genes likely associated with the fruit acidity control. PMID:27092171

Hello! Kids Network around the World.

ERIC Educational Resources Information Center

Lynes, Kristine

1996-01-01

Describes Kids Network, an educational network available from the National Geographic Society that allows students in grades four through six to become part of research teams that include students from around the world. Computer hardware requirements and a list of Kids Network research questions are listed in a sidebar. (JMV)

Partnership disengagement from primary community care networks (PCCNs): A qualitative study for a national demonstration project

PubMed Central

2010-01-01

Background The Primary Community Care Network (PCCN) Demonstration Project, launched by the Bureau of National Health Insurance (BNHI) in 2003, is still in progress. Partnership structures in PCCNs represent both contractual clinic-to-clinic and clinic-to-hospital member relationships of organizational aspects. The partnership structures are the formal relationships between individuals and the total network. Their organizational design aims to ensure effective communication, coordination, and integration across the total network. Previous studies have focused largely on how contractual integration among the partnerships works and on its effects. Few studies, however, have tried to understand partnership disengagement in PCCNs. This study explores why some partnerships in PCCNs disengage. Methods This study used a qualitative methodology with semi-structured questions for in-depth interviews. The semi-structured questions were pre-designed to explore the factors driving partnership disengagement. Thirty-seven clinic members who had withdrawn from their PCCNs were identified from the 2003-2005 Taiwan Primary Community Care Network Lists. Results Organization/participant factors (extra working time spend and facility competency), network factors (partner collaboration), and community factors (health policy design incompatibility, patient-physician relationship, and effectiveness) are reasons for clinic physicians to withdraw or change their partnerships within the PCCNs. Conclusions To strengthen partnership relationships, several suggestions are made, including to establish clinic and hospital member relationships, and to reduce administrative work. In addition, both educating the public about the concept of family doctors and ensuring well-organized national health policies could help health care providers improve the integration processes. PMID:20359369

Integrated situational awareness for cyber attack detection, analysis, and mitigation

NASA Astrophysics Data System (ADS)

Cheng, Yi; Sagduyu, Yalin; Deng, Julia; Li, Jason; Liu, Peng

2012-06-01

Real-time cyberspace situational awareness is critical for securing and protecting today's enterprise networks from various cyber threats. When a security incident occurs, network administrators and security analysts need to know what exactly has happened in the network, why it happened, and what actions or countermeasures should be taken to quickly mitigate the potential impacts. In this paper, we propose an integrated cyberspace situational awareness system for efficient cyber attack detection, analysis and mitigation in large-scale enterprise networks. Essentially, a cyberspace common operational picture will be developed, which is a multi-layer graphical model and can efficiently capture and represent the statuses, relationships, and interdependencies of various entities and elements within and among different levels of a network. Once shared among authorized users, this cyberspace common operational picture can provide an integrated view of the logical, physical, and cyber domains, and a unique visualization of disparate data sets to support decision makers. In addition, advanced analyses, such as Bayesian Network analysis, will be explored to address the information uncertainty, dynamic and complex cyber attack detection, and optimal impact mitigation issues. All the developed technologies will be further integrated into an automatic software toolkit to achieve near real-time cyberspace situational awareness and impact mitigation in large-scale computer networks.

Social networks and health policy: the case of misoprostol and the WHO model essential medicine list.

PubMed

Millard, Colin; Brhlikova, Petra; Pollock, Allyson

2015-05-01

The WHO Essential Medicines List (EML) was established to help countries prioritise medicines according to their health care needs. Selection for the List is based on rigorous scrutiny of public health relevance, evidence on efficacy and safety, and comparative cost effectiveness. The WHO ideal is that a medicine and its efficacy are based on science, but in reality a medicine has a social life and the acceptance of a pharmaceutical intervention involves the interaction of a wide array of governmental and civil society organisations, and industry. Misoprostol is a medicine widely used for both abortion and prevention of postpartum haemorrhage in low income countries. Although the evidence for the latter is highly contested it was nevertheless added to the WHO EML in 2011. We use social network analysis to examine the social, political and economic field surrounding the WHO EML applications and health policy. We describe a chronology of the drug's use and of the applications to the WHO EML and carry out a social network analysis of the organisations and individuals involved in the applications, research and dissemination. The research identified a network of 238 organisations and individuals involved in the promotion of misoprostol for postpartum haemorrhage and present at the time of the WHO EML applications. There is a strong interdependency between the funding bodies, civil society organisations, researchers and clinician organisations. The research was part of an EU FP7 funded project on Accessing Medicines in Africa and South Asia (2010-2013). Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

Science and ethics meet: a mathematical view on one kind of violation of publication ethics

NASA Astrophysics Data System (ADS)

Shinyaeva, Taisiya S.; Tarasevich, Yuri Yu

2018-01-01

When a person who did not make a significant intellectual contribution to a published research is included into the co-author list, the person is called gift or guest author depending on the reason why the person has been added to the co-authors. Essential deviation of properties of a particular co-author network from typical values may evidenced that the network is artificial. Using network analysis, we have performed an attempt to characterize a typical co-author network. We performed analysis of the co-author networks using references in the thesis on Physics and Mathematics, Economics defended from 2012 to 2017 and planned to be defended in 2017 and 2018 in Russia. Properties of the co-author networks are expected to be a reference sample in future research.

Atmospheric Hydrogen (H2) Concentrations from the CSIRO GASLAB Flask Sampling Network (1992 - 2001)

DOE Data Explorer

Steele, L. P. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia; Krummel, P. B. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia; Langenfelds, R. L. [Commonwealth Scientific and Industrial Research Organization (CSIRO), Atmospheric Research, Aspendale, Victoria, Australia

2003-01-01

Air samples from nine sites were collected from the CSIRO GASLAB Flask Sampling Network for the purpose of monitoring the atmospheric hydrogen (H2) concentrations. The listed data were obtained from flask air samples returned to the CSIRO GASLAB for analysis. Typical sample storage times ranged from days to weeks for some sites (e.g., Cape Grim) to as much as one year for Macquarie Island and the Antarctic sites. Experiments carried out to test for any change in sample H22 mixing ratio during storage have shown no consistent and systematic drift in these flask types over test periods of several months to years (Cooper et al., 1999). An annual cycle of H2 is evident, reflecting the seasonal nature of some of the major sources and sinks (Novelli et al., 1999).

Construction of an integrated gene regulatory network link to stress-related immune system in cattle.

PubMed

Behdani, Elham; Bakhtiarizadeh, Mohammad Reza

2017-10-01

The immune system is an important biological system that is negatively impacted by stress. This study constructed an integrated regulatory network to enhance our understanding of the regulatory gene network used in the stress-related immune system. Module inference was used to construct modules of co-expressed genes with bovine leukocyte RNA-Seq data. Transcription factors (TFs) were then assigned to these modules using Lemon-Tree algorithms. In addition, the TFs assigned to each module were confirmed using the promoter analysis and protein-protein interactions data. Therefore, our integrated method identified three TFs which include one TF that is previously known to be involved in immune response (MYBL2) and two TFs (E2F8 and FOXS1) that had not been recognized previously and were identified for the first time in this study as novel regulatory candidates in immune response. This study provides valuable insights on the regulatory programs of genes involved in the stress-related immune system.

CPTAC Teams | Office of Cancer Clinical Proteomics Research

Cancer.gov

The following are the current CPTAC teams, representing a network of Proteome Characterization Centers (PCCs), Proteogenomic Translational Research Centers (PTRCs), and Proteogenomic Data Analysis Centers (PGDACs). Teams are listed alphabetically by institution, with their respective Principal Investigators:

Definition, analysis and development of an optical data distribution network for integrated avionics and control systems. Part 2: Component development and system integration

NASA Technical Reports Server (NTRS)

Yen, H. W.; Morrison, R. J.

1984-01-01

Fiber optic transmission is emerging as an attractive concept in data distribution onboard civil aircraft. Development of an Optical Data Distribution Network for Integrated Avionics and Control Systems for commercial aircraft will provide a data distribution network that gives freedom from EMI-RFI and ground loop problems, eliminates crosstalk and short circuits, provides protection and immunity from lightning induced transients and give a large bandwidth data transmission capability. In addition there is a potential for significantly reducing the weight and increasing the reliability over conventional data distribution networks. Wavelength Division Multiplexing (WDM) is a candidate method for data communication between the various avionic subsystems. With WDM all systems could conceptually communicate with each other without time sharing and requiring complicated coding schemes for each computer and subsystem to recognize a message. However, the state of the art of optical technology limits the application of fiber optics in advanced integrated avionics and control systems. Therefore, it is necessary to address the architecture for a fiber optics data distribution system for integrated avionics and control systems as well as develop prototype components and systems.

Ties that Bind: A Social Network Approach To Understanding Student Integration and Persistence.

ERIC Educational Resources Information Center

Thomas, Scott L.

2000-01-01

This study used a social network paradigm to examine college student integration of 329 college freshmen at a private liberal arts college. Analysis of the structural aspects of students' on-campus associations found differential effects of various social network characteristics on student commitment and persistence. (DB)

47 CFR 73.1212 - Sponsorship identification; list retention; related requirements.

Code of Federal Regulations, 2011 CFR

2011-10-01

... 47 Telecommunication 4 2011-10-01 2011-10-01 false Sponsorship identification; list retention; related requirements. 73.1212 Section 73.1212 Telecommunication FEDERAL COMMUNICATIONS COMMISSION... network, the list may, instead, be retained at the headquarters office of the network or at the location...

Monitoring Malware Activity on the LAN Network

NASA Astrophysics Data System (ADS)

Skrzewski, Mirosław

Many security related organizations periodically publish current network and systems security information, with the lists of top malware programs. These lists raises the question how these threats spreads out, if the worms (the only threat with own communication abilities) are low or missing on these lists. The paper discuss the research on malware network activity, aimed to deliver the answer to the question, what is the main infection channel of modern malware, done with the usage of virtual honeypot systems on dedicated, unprotected network. Systems setup, network and systems monitoring solutions, results of over three months of network traffic and malware monitoring are presented, along with the proposed answer to our research question.

Ontology-supported research on vaccine efficacy, safety and integrative biological networks.

PubMed

He, Yongqun

2014-07-01

While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including Vaccine Ontology, Ontology of Adverse Events and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network ('OneNet') Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms.

Ontology-supported Research on Vaccine Efficacy, Safety, and Integrative Biological Networks

PubMed Central

He, Yongqun

2016-01-01

Summary While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including the Vaccine Ontology, Ontology of Adverse Events, and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network (“OneNet”) Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms. PMID:24909153

Comparison of risk factors and outcomes for pediatric patients listed for heart transplantation after bidirectional Glenn and after Fontan: an analysis from the Pediatric Heart Transplant Study.

PubMed

Kovach, Joshua R; Naftel, David C; Pearce, F Bennett; Tresler, Margaret A; Edens, R Erik; Shuhaiber, Jeffrey H; Blume, Elizabeth D; Fynn-Thompson, Francis; Kirklin, James K; Zangwill, Steven D

2012-02-01

Patients listed for transplant after the bidirectional Glenn (BDG) may have better outcomes than patients listed after Fontan. This study examined and compared outcomes after listing for BDG and Fontan patients. All patients listed for transplant after the BDG in the Pediatric Heart Transplant Study between January 1993 and December 2008 were evaluated. Comparisons were made with Fontan patients and with a matched cohort of congenital heart disease patients. Competing outcomes analysis and actuarial survival were evaluated for the study populations, including an examination of various risk factors. Competing outcomes analysis for BDG and Fontan patients after listing were similar. There was no difference in actuarial survival after listing or transplant among the 3 cohorts. Mechanical ventilation, United Network of Organ Sharing status, and age were risk factors for death after listing in BDG and Fontan patients, but ventilation at the time of transplant was significant only for the Fontan patients. Mortality was increased in Fontan patients listed < 6 months after surgery compared with patients listed > 6 months after surgery, but no difference was observed in BDG patients. There was a trend toward improved survival after listing for both populations across 3 eras of the study, but this did not reach statistical significance. Outcomes after listing for BDG and Fontan patients are similar. Mechanical ventilation at the time of transplant remains a significant risk factor for death in the Fontan population, as does listing for transplant soon after the Fontan, suggesting that some patients may benefit from transplant instead of Fontan completion. Copyright © 2012 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Analysis of integrated healthcare networks' performance: a contingency-strategic management perspective.

PubMed

Lin, B Y; Wan, T T

1999-12-01

Few empirical analyses have been done in the organizational researches of integrated healthcare networks (IHNs) or integrated healthcare delivery systems. Using a contingency derived contact-process-performance model, this study attempts to explore the relationships among an IHN's strategic direction, structural design, and performance. A cross-sectional analysis of 100 IHNs suggests that certain contextual factors such as market competition and network age and tax status have statistically significant effects on the implementation of an IHN's service differentiation strategy, which addresses coordination and control in the market. An IHN's service differentiation strategy is positively related to its integrated structural design, which is characterized as integration of administration, patient care, and information system across different settings. However, no evidence supports that the development of integrated structural design may benefit an IHN's performance in terms of clinical efficiency and financial viability.

Dependable Emergency-Response Networking Based on Retaskable Network Infrastructures

DTIC Science & Technology

2008-04-01

a Focus Group for the National Reliability and Interoperability Council (NRIC VII), which has helped to suggest a list of possible types of agents...APR 2008 2. REPORT TYPE N/A 3. DATES COVERED - 4. TITLE AND SUBTITLE Dependable Emergency-Response Networking Based on Retaskable Network...of his network op- timization algorithms. We would like to thank the TCIP Center team for their feed- back on this work. This work was supported in

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios

PubMed Central

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-01-01

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN. PMID:26593919

Capacity Model and Constraints Analysis for Integrated Remote Wireless Sensor and Satellite Network in Emergency Scenarios.

PubMed

Zhang, Wei; Zhang, Gengxin; Dong, Feihong; Xie, Zhidong; Bian, Dongming

2015-11-17

This article investigates the capacity problem of an integrated remote wireless sensor and satellite network (IWSSN) in emergency scenarios. We formulate a general model to evaluate the remote sensor and satellite network capacity. Compared to most existing works for ground networks, the proposed model is time varying and space oriented. To capture the characteristics of a practical network, we sift through major capacity-impacting constraints and analyze the influence of these constraints. Specifically, we combine the geometric satellite orbit model and satellite tool kit (STK) engineering software to quantify the trends of the capacity constraints. Our objective in analyzing these trends is to provide insights and design guidelines for optimizing the integrated remote wireless sensor and satellite network schedules. Simulation results validate the theoretical analysis of capacity trends and show the optimization opportunities of the IWSSN.

A randomized wait-list controlled analysis of the implementation integrity of team-initiated problem solving processes.

PubMed

Newton, J Stephen; Horner, Robert H; Algozzine, Bob; Todd, Anne W; Algozzine, Kate

2012-08-01

Members of Positive Behavior Interventions and Supports (PBIS) teams from 34 elementary schools participated in a Team-Initiated Problem Solving (TIPS) Workshop and follow-up technical assistance. Within the context of a randomized wait-list controlled trial, team members who were the first recipients of the TIPS intervention demonstrated greater implementation integrity in using the problem-solving processes during their team meetings than did members of PBIS Teams in the Wait-List Control group. The success of TIPS at improving implementation integrity of the problem-solving processes is encouraging and suggests the value of conducting additional research focused on determining whether there is a functional relation between use of these problem-solving processes and actual resolution of targeted student academic and social problems. Copyright © 2012 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer.

PubMed

Pineda, Silvia; Van Steen, Kristel; Malats, Núria

2017-09-01

Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative-expression quantitative trait loci (eQTL) analysis applying two-stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model were then regressed with the germline genotypes measured in blood. Previously, we demonstrated that penalized regression methods in combination with a permutation-based MaxT method (Global-LASSO) is a promising tool to fix some of the challenges that high-throughput omics data analysis imposes. Here, we assessed whether Global-LASSO can also be applied when tumor and blood omics data are integrated. We further compared our strategy with two 2SR-approaches, one using multiple linear regression (2SR-MLR) and other using LASSO (2SR-LASSO). We applied the three models to integrate genomic, epigenomic, and transcriptomic data from tumor tissue with blood germline genotypes from 181 individuals with bladder cancer included in the TCGA Consortium. Global-LASSO provided a larger list of eQTLs than the 2SR methods, identified a previously reported eQTLs in prostate stem cell antigen (PSCA), and provided further clues on the complexity of APBEC3B loci, with a minimal false-positive rate not achieved by 2SR-MLR. It also represents an important contribution for omics integrative analysis because it is easy to apply and adaptable to any type of data. © 2017 WILEY PERIODICALS, INC.

Discover mouse gene coexpression landscapes using dictionary learning and sparse coding.

PubMed

Li, Yujie; Chen, Hanbo; Jiang, Xi; Li, Xiang; Lv, Jinglei; Peng, Hanchuan; Tsien, Joe Z; Liu, Tianming

2017-12-01

Gene coexpression patterns carry rich information regarding enormously complex brain structures and functions. Characterization of these patterns in an unbiased, integrated, and anatomically comprehensive manner will illuminate the higher-order transcriptome organization and offer genetic foundations of functional circuitry. Here using dictionary learning and sparse coding, we derived coexpression networks from the space-resolved anatomical comprehensive in situ hybridization data from Allen Mouse Brain Atlas dataset. The key idea is that if two genes use the same dictionary to represent their original signals, then their gene expressions must share similar patterns, thereby considering them as "coexpressed." For each network, we have simultaneous knowledge of spatial distributions, the genes in the network and the extent a particular gene conforms to the coexpression pattern. Gene ontologies and the comparisons with published gene lists reveal biologically identified coexpression networks, some of which correspond to major cell types, biological pathways, and/or anatomical regions.

Field Instrumentation With Bricks: Wireless Networks Built From Tough, Cheap, Reliable Field Computers

NASA Astrophysics Data System (ADS)

Fatland, D. R.; Anandakrishnan, S.; Heavner, M.

2004-12-01

We describe tough, cheap, reliable field computers configured as wireless networks for distributed high-volume data acquisition and low-cost data recovery. Running under the GNU/Linux open source model these network nodes ('Bricks') are intended for either autonomous or managed deployment for many months in harsh Arctic conditions. We present here results from Generation-1 Bricks used in 2004 for glacier seismology research in Alaska and Antarctica and describe future generation Bricks in terms of core capabilities and a growing list of field applications. Subsequent generations of Bricks will feature low-power embedded architecture, large data storage capacity (GB), long range telemetry (15 km+ up from 3 km currently), and robust operational software. The list of Brick applications is growing to include Geodetic GPS, Bioacoustics (bats to whales), volcano seismicity, tracking marine fauna, ice sounding via distributed microwave receivers and more. This NASA-supported STTR project capitalizes on advancing computer/wireless technology to get scientists more data per research budget dollar, solving system integration problems and thereby getting researchers out of the hardware lab and into the field. One exemplary scenario: An investigator can install a Brick network in a remote polar environment to collect data for several months and then fly over the site to recover the data via wireless telemetry. In the past year Brick networks have moved beyond proof-of-concept to the full-bore development and testing stage; they will be a mature and powerful tool available for IPY 2007-8.

Metabolic Networks Integrative Cardiac Health Project (ICHP) - Center of Excellence

DTIC Science & Technology

2016-04-01

2.6; P = 0.001) among all variables, as the most significant predictor of abnormal CIMT, thus increasing risk for CVD. Conclusions: The Integrative ...1 Award Number: W81XWH-11-2-0227 TITLE: "Metabolic Networks Integrative Cardiac Health Project (ICHP) - Center of Excellence." PRINCIPAL...April 2016 2. REPORT TYPE ANNUAL 3. DATES COVERED (From - To) 4. TITLE AND SUBTITLE "Metabolic Networks Integrative Cardiac Health Project (ICHP

European Extremely Large Telescope (E-ELT) availability stochastic model: integrating failure mode and effect analysis (FMEA), influence diagram, and Bayesian network together

NASA Astrophysics Data System (ADS)

Verzichelli, Gianluca

2016-08-01

An Availability Stochastic Model for the E-ELT has been developed in GeNIE. The latter is a Graphical User Interface (GUI) for the Structural Modeling, Inference, and Learning Engine (SMILE), originally distributed by the Decision Systems Laboratory from the University of Pittsburgh, and now being a product of Bayes Fusion, LLC. The E-ELT will be the largest optical/near-infrared telescope in the world. Its design comprises an Alt-Azimuth mount reflecting telescope with a 39-metre-diameter segmented primary mirror, a 4-metre-diameter secondary mirror, a 3.75-metre-diameter tertiary mirror, adaptive optics and multiple instruments. This paper highlights how a Model has been developed for an earlier on assessment of the Telescope Avail- ability. It also describes the modular structure and the underlying assumptions that have been adopted for developing the model and demonstrates the integration of FMEA, Influence Diagram and Bayesian Network elements. These have been considered for a better characterization of the Model inputs and outputs and for taking into account Degraded-based Reliability (DBR). Lastly, it provides an overview of how the information and knowledge captured in the model may be used for an earlier on definition of the Failure, Detection, Isolation and Recovery (FDIR) Control Strategy and the Telescope Minimum Master Equipment List (T-MMEL).

Second Language Word Learning through Repetition and Imitation: Functional Networks as a Function of Learning Phase and Language Distance.

PubMed

Ghazi-Saidi, Ladan; Ansaldo, Ana Ines

2017-01-01

Introduction and Aim : Repetition and imitation are among the oldest second language (L2) teaching approaches and are frequently used in the context of L2 learning and language therapy, despite some heavy criticism. Current neuroimaging techniques allow the neural mechanisms underlying repetition and imitation to be examined. This fMRI study examines the influence of verbal repetition and imitation on network configuration. Integration changes within and between the cognitive control and language networks were studied, in a pair of linguistically close languages (Spanish and French), and compared to our previous work on a distant language pair (Ghazi-Saidi et al., 2013). Methods : Twelve healthy native Spanish-speaking (L1) adults, and 12 healthy native Persian-speaking adults learned 130 new French (L2) words, through a computerized audiovisual repetition and imitation program. The program presented colored photos of objects. Participants were instructed to look at each photo and pronounce its name as closely as possible to the native template (imitate). Repetition was encouraged as many times as necessary to learn the object's name; phonological cues were provided if necessary. Participants practiced for 15 min, over 30 days, and were tested while naming the same items during fMRI scanning, at week 1 (shallow learning phase) and week 4 (consolidation phase) of training. To compare this set of data with our previous work on Persian speakers, a similar data analysis plan including accuracy rates (AR), response times (RT), and functional integration values for the language and cognitive control network at each measure point was included, with further L1-L2 direct comparisons across the two populations. Results and Discussion : The evidence shows that learning L2 words through repetition induces neuroplasticity at the network level. Specifically, L2 word learners showed increased network integration after 3 weeks of training, with both close and distant language pairs. Moreover, higher network integration was observed in the learners with the close language pair, suggesting that repetition effects on network configuration vary as a function of task complexity.

A one-day centralized work-up for kidney transplant recipient candidates: a quality improvement report.

PubMed

Formica, Richard N; Barrantes, Fidel; Asch, William S; Bia, Margaret J; Coca, Steven; Kalyesubula, Robert; McCloskey, Barbara; Leary, Tucker; Arvelakis, Antonios; Kulkarni, Sanjay

2012-08-01

Waiting time for a kidney transplant is calculated from the date the patient is placed on the UNOS (United Network for Organ Sharing) waitlist to the date the patient undergoes transplant. Time from transplant evaluation to listing represents unaccounted waiting time, potentially resulting in longer dialysis exposure for some patients with prolonged evaluation times. There are established disparities demonstrating that groups of patients take longer to be placed on the waitlist and thus have less access to kidney transplant. Quality improvement report. 905 patients from a university-based hospital were evaluated for kidney transplant candidacy, and analysis was performed from July 1, 2004, to January 31, 2010. A 1-day centralized work-up was implemented on July 1, 2007, whereby the transplant center coordinated the necessary tests needed to fulfill minimal listing criteria. Time from evaluation to UNOS listing was compared between the 2 cohorts. Multivariable Cox proportional hazards models were created to assess the relative hazards of waitlist placement comparing 1-day versus conventional work-up and were adjusted for age, sex, race, and education. Of 905 patients analyzed, 378 underwent conventional evaluation and 527 underwent a 1-day center-coordinated evaluation. Median time to listing in the 1-day center-coordinated evaluation compared with conventional was significantly less (46 vs 226 days, P < 0.001). On multivariable analysis controlling for age, sex, and education level, the 1-day in-center group was 3 times more likely to place patients on the wait list (adjusted HR, 3.08; 95% CI, 2.64-3.59). Listing time was significantly decreased across race, sex, education, and ethnicity. Single center, retrospective. Variables that may influence transplant practitioners, such as comorbid conditions or functional status, were not assessed. A 1-day center-coordinated pretransplant work-up model significantly decreased time to listing for kidney transplant. Copyright © 2012 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Systematic analysis of molecular mechanisms for HCC metastasis via text mining approach.

PubMed

Zhen, Cheng; Zhu, Caizhong; Chen, Haoyang; Xiong, Yiru; Tan, Junyuan; Chen, Dong; Li, Jin

2017-02-21

To systematically explore the molecular mechanism for hepatocellular carcinoma (HCC) metastasis and identify regulatory genes with text mining methods. Genes with highest frequencies and significant pathways related to HCC metastasis were listed. A handful of proteins such as EGFR, MDM2, TP53 and APP, were identified as hub nodes in PPI (protein-protein interaction) network. Compared with unique genes for HBV-HCCs, genes particular to HCV-HCCs were less, but may participate in more extensive signaling processes. VEGFA, PI3KCA, MAPK1, MMP9 and other genes may play important roles in multiple phenotypes of metastasis. Genes in abstracts of HCC-metastasis literatures were identified. Word frequency analysis, KEGG pathway and PPI network analysis were performed. Then co-occurrence analysis between genes and metastasis-related phenotypes were carried out. Text mining is effective for revealing potential regulators or pathways, but the purpose of it should be specific, and the combination of various methods will be more useful.

Basic Student Charges at Postsecondary Institutions: Academic Year 1994-95. Tuition and Required Fees and Room and Board Charges at 4-Year, 2-Year, and Public Less-Than-2-Year Institutions. Statistical Analysis Report.

ERIC Educational Resources Information Center

Barbett, Samuel F.; And Others

This document lists the typical tuition and required fees and room and board charges assessed to college students in 1994-95 based on a national "Institutional Characteristics" survey which is part of the Integrated Postsecondary Education Data System. The data were collected from over 5,000 of the 5,775 4-year, 2-year, and public…

The Potential Impact of a “No-Buy” List on Youth Exposure to Alcohol Advertising on Cable Television

PubMed Central

Ross, Craig S.; Brewer, Robert D.; Jernigan, David H.

2016-01-01

Objective: The purpose of this study was to outline a method to improve alcohol industry compliance with its self-regulatory advertising placement guidelines on television with the goal of reducing youth exposure to noncompliant advertisements. Method: Data were sourced from Nielsen (The Nielsen Company, New York, NY) for all alcohol advertisements on television in the United States for 2005–2012. A “no-buy” list, that is a list of cable television programs and networks to be avoided when purchasing alcohol advertising, was devised using three criteria: avoid placements on programs that were noncompliant in the past (serially noncompliant), avoid placements on networks at times of day when youth make up a high proportion of the audience (high-risk network dayparts), and use a “guardbanded” (or more restrictive) composition guideline when placing ads on low-rated programs (low rated). Results: Youth were exposed to 15.1 billion noncompliant advertising impressions from 2005 to 2012, mostly on cable television. Together, the three no-buy list criteria accounted for 99% of 12.9 billion noncompliant advertising exposures on cable television for youth ages 2–20 years. When we evaluated the no-buy list criteria sequentially and mutually exclusively, serially noncompliant ads accounted for 67% of noncompliant exposure, high-risk network-daypart ads accounted for 26%, and low rated ads accounted for 7%. Conclusions: These findings suggest that the prospective use of the no-buy list criteria when purchasing alcohol advertising could eliminate most noncompliant advertising exposures and could be incorporated into standard post-audit procedures that are widely used by the alcohol industry in assessing exposure to television advertising. PMID:26751350

Social support network, mental health and quality of life: a cross-sectional study in primary care.

PubMed

Portugal, Flávia Batista; Campos, Mônica Rodrigues; Correia, Celina Ragoni; Gonçalves, Daniel Almeida; Ballester, Dinarte; Tófoli, Luis Fernando; Mari, Jair de Jesus; Gask, Linda; Dowrick, Christopher; Bower, Peter; Fortes, Sandra

2016-12-22

The objective of this study was to identify the association between emotional distress and social support networks with quality of life in primary care patients. This was a cross-sectional study involving 1,466 patients in the cities of São Paulo and Rio de Janeiro, Brazil, in 2009/2010. The General Health Questionnaire, the Hospital Anxiety and Depression Scale and the brief version of the World Health Organization Quality of Life Instrument were used. The Social Support Network Index classified patients with the highest and lowest index as socially integrated or isolated. A bivariate analysis and four multiple linear regressions were conducted for each quality of life outcome. The means scores for the physical, psychological, social relations, and environment domains were, respectively, 64.7; 64.2; 68.5 and 49.1. In the multivariate analysis, the psychological domain was negatively associated with isolation, whereas the social relations and environment domains were positively associated with integration. Integration and isolation proved to be important factors for those in emotional distress as they minimize or maximize negative effects on quality of life.

Microcomputer Network for Computerized Adaptive Testing (CAT): Program Listing. Supplement.

DTIC Science & Technology

1984-03-01

UMICROCOMPUTER NETWORK FOR COMPUTERIZED ADAPTIVE TESTING ( CAT ): PROGRAM LISTING in APPROVED FOR PUBLIC RELEASE;IDISTRIBUTION UNLIMITEDPs DTIC ’ Akf 3 0 1-d84...NETWORK FOR COMPUTERIZED ADAPTIVE TESTING ( CAT ).- PROGRAM LISTING , ,j Baldwin Quan Thomas A. Park Gary Sandahl John H. Wolfe Reviewed by James R. McBride A...Center San Diego, California 92152 V.% :-, CONTENTrS Page CATPROJECT.TEXT CAT system driver textfile I 1 ADMINDIR- Subdirectory - Test administration

A Requirements Analysis for an Integrated Maintenance Information System Application Into Theater Air Control System Maintenance

DTIC Science & Technology

1994-09-01

133 v List of Tables Table Page 1. Line Item Changes in Proposed Ground TACS SSS Matrix...39 2. Percentage of Line Item Changes in Proposed SSS Matrix for G round T A C S...modified to meet Theater Air Control System requirements. The small amount of changes required to modify the aircraft matrix in order to satisfy ground

Computational Tools for Metabolic Engineering

PubMed Central

Copeland, Wilbert B.; Bartley, Bryan A.; Chandran, Deepak; Galdzicki, Michal; Kim, Kyung H.; Sleight, Sean C.; Maranas, Costas D.; Sauro, Herbert M.

2012-01-01

A great variety of software applications are now employed in the metabolic engineering field. These applications have been created to support a wide range of experimental and analysis techniques. Computational tools are utilized throughout the metabolic engineering workflow to extract and interpret relevant information from large data sets, to present complex models in a more manageable form, and to propose efficient network design strategies. In this review, we present a number of tools that can assist in modifying and understanding cellular metabolic networks. The review covers seven areas of relevance to metabolic engineers. These include metabolic reconstruction efforts, network visualization, nucleic acid and protein engineering, metabolic flux analysis, pathway prospecting, post-structural network analysis and culture optimization. The list of available tools is extensive and we can only highlight a small, representative portion of the tools from each area. PMID:22629572

Strategic Mobility 21: Integrated Tracking System Analysis and Concept Design

DTIC Science & Technology

2007-08-31

public and foreign nationals, companies, and governments , including adversary governments , and may be exported. c. This statement may not be used on...42 ii Integrated Tracking System Analysis & Concept Design LIST OF FIGURES Figure 1: Southern California Association of Governments ...conducted under the auspices of the California State University – Long Beach Foundation, a government -industry academic collaborative enterprise

Integrated network analysis reveals potentially novel molecular mechanisms and therapeutic targets of refractory epilepsies

PubMed Central

Liu, Guangming; Wang, Yiwei; Zhao, Pengyao; Zhu, Yizhun; Yang, Xiaohan; Zheng, Tiezheng; Zhou, Xuezhong; Jin, Weilin; Sun, Changkai

2017-01-01

Epilepsy is a complex neurological disorder and a significant health problem. The pathogenesis of epilepsy remains obscure in a significant number of patients and the current treatment options are not adequate in about a third of individuals which were known as refractory epilepsies (RE). Network medicine provides an effective approach for studying the molecular mechanisms underlying complex diseases. Here we integrated 1876 disease-gene associations of RE and located those genes to human protein-protein interaction (PPI) network to obtain 42 significant RE-associated disease modules. The functional analysis of these disease modules showed novel molecular pathological mechanisms of RE, such as the novel enriched pathways (e.g., “presynaptic nicotinic acetylcholine receptors”, “signaling by insulin receptor”). Further analysis on the relationships between current drug targets and the RE-related disease genes showed the rational mechanisms of most antiepileptic drugs. In addition, we detected ten potential novel drug targets (e.g., KCNA1, KCNA4-6, KCNC3, KCND2, KCNMA1, CAMK2G, CACNB4 and GRM1) located in three RE related disease modules, which might provide novel insights into the new drug discovery for RE therapy. PMID:28388656

Investigation of candidate genes for osteoarthritis based on gene expression profiles.

PubMed

Dong, Shuanghai; Xia, Tian; Wang, Lei; Zhao, Qinghua; Tian, Jiwei

2016-12-01

To explore the mechanism of osteoarthritis (OA) and provide valid biological information for further investigation. Gene expression profile of GSE46750 was downloaded from Gene Expression Omnibus database. The Linear Models for Microarray Data (limma) package (Bioconductor project, http://www.bioconductor.org/packages/release/bioc/html/limma.html) was used to identify differentially expressed genes (DEGs) in inflamed OA samples. Gene Ontology function enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways enrichment analysis of DEGs were performed based on Database for Annotation, Visualization and Integrated Discovery data, and protein-protein interaction (PPI) network was constructed based on the Search Tool for the Retrieval of Interacting Genes/Proteins database. Regulatory network was screened based on Encyclopedia of DNA Elements. Molecular Complex Detection was used for sub-network screening. Two sub-networks with highest node degree were integrated with transcriptional regulatory network and KEGG functional enrichment analysis was processed for 2 modules. In total, 401 up- and 196 down-regulated DEGs were obtained. Up-regulated DEGs were involved in inflammatory response, while down-regulated DEGs were involved in cell cycle. PPI network with 2392 protein interactions was constructed. Moreover, 10 genes including Interleukin 6 (IL6) and Aurora B kinase (AURKB) were found to be outstanding in PPI network. There are 214 up- and 8 down-regulated transcription factor (TF)-target pairs in the TF regulatory network. Module 1 had TFs including SPI1, PRDM1, and FOS, while module 2 contained FOSL1. The nodes in module 1 were enriched in chemokine signaling pathway, while the nodes in module 2 were mainly enriched in cell cycle. The screened DEGs including IL6, AGT, and AURKB might be potential biomarkers for gene therapy for OA by being regulated by TFs such as FOS and SPI1, and participating in the cell cycle and cytokine-cytokine receptor interaction pathway. Copyright © 2016 Turkish Association of Orthopaedics and Traumatology. Production and hosting by Elsevier B.V. All rights reserved.

System of Systems Engineering and Integration Process for Network Transport Assessment

DTIC Science & Technology

2016-09-01

SOSE&I CONCEPTS The DOD-sourced “Systems Engineering Guide for Systems of Systems” provides an overview of the SoS environment and SE considerations...usage as a guide in application of systems engineering processes. They are listed verbatim below as defined in the DOD SE guide (ODUSD[A&T]SSE 2008...Technology (A&T), Systems and Software Engineering (SSE). 2008. Systems Engineering Guide for Systems of Systems. Washington, DC: ODUSD(A&T)SSE

Analysis of the effects of geological and geomorphological factors on earthquake triggered landslides using artificial neural networks (ANN)

NASA Astrophysics Data System (ADS)

Kawabata, D.; Bandibas, J.

2007-12-01

The occurrence of landslide is the result of the interaction of complex and diverse environmental factors. The geomorphic and geologic features, rock types and vegetative cover are important base factors of landslide occurrence. However, determining the relationship between these factors and landslide occurrence is very difficult using conventional mathematical analysis. The use of an advanced computing technique for this kind of analysis is very important. Artificial neural network (ANN) has recently been included in the list of analytical tools for a wide range of applications in the natural sciences research fields. One of the advantages of using ANN for pattern recognition is that it can handle data at any measurement scale ranging from nominal, ordinal to linear and ratio, and any form of data distribution (Wang et al., 1995). In addition, it can easily handle qualitative variables making it widely used in integrated analysis of spatial data from multiple sources for predicting and classification. This study focuses on the definition of the relationship between geological factors and landslide occurrence using artificial neural networks. The study also focuses on the effect of the DTMs (e.g. ASTER DTM, ALSM, digitized from paper map and digital photogrammetric measurement data). The main aim of the study is to generate landslide susceptibility index map using the defined relationship using ANN. Landslide data in the Chuetsu region were used in this research. The 2004 earthquake triggered many landslides in the region. The initial results of the study showed that ANN is more accurate in defining the relationship between geological and geomorphological factors and landslide occurrence. It also determined the best combination of geological and geomorphological factors that is directly related to landslide occurrence.

Integration of Network Biology and Imaging to Study Cancer Phenotypes and Responses.

PubMed

Tian, Ye; Wang, Sean S; Zhang, Zhen; Rodriguez, Olga C; Petricoin, Emanuel; Shih, Ie-Ming; Chan, Daniel; Avantaggiati, Maria; Yu, Guoqiang; Ye, Shaozhen; Clarke, Robert; Wang, Chao; Zhang, Bai; Wang, Yue; Albanese, Chris

2014-01-01

Ever growing "omics" data and continuously accumulated biological knowledge provide an unprecedented opportunity to identify molecular biomarkers and their interactions that are responsible for cancer phenotypes that can be accurately defined by clinical measurements such as in vivo imaging. Since signaling or regulatory networks are dynamic and context-specific, systematic efforts to characterize such structural alterations must effectively distinguish significant network rewiring from random background fluctuations. Here we introduced a novel integration of network biology and imaging to study cancer phenotypes and responses to treatments at the molecular systems level. Specifically, Differential Dependence Network (DDN) analysis was used to detect statistically significant topological rewiring in molecular networks between two phenotypic conditions, and in vivo Magnetic Resonance Imaging (MRI) was used to more accurately define phenotypic sample groups for such differential analysis. We applied DDN to analyze two distinct phenotypic groups of breast cancer and study how genomic instability affects the molecular network topologies in high-grade ovarian cancer. Further, FDA-approved arsenic trioxide (ATO) and the ND2-SmoA1 mouse model of Medulloblastoma (MB) were used to extend our analyses of combined MRI and Reverse Phase Protein Microarray (RPMA) data to assess tumor responses to ATO and to uncover the complexity of therapeutic molecular biology.

Analysis of adaptive algorithms for an integrated communication network

NASA Technical Reports Server (NTRS)

Reed, Daniel A.; Barr, Matthew; Chong-Kwon, Kim

1985-01-01

Techniques were examined that trade communication bandwidth for decreased transmission delays. When the network is lightly used, these schemes attempt to use additional network resources to decrease communication delays. As the network utilization rises, the schemes degrade gracefully, still providing service but with minimal use of the network. Because the schemes use a combination of circuit and packet switching, they should respond to variations in the types and amounts of network traffic. Also, a combination of circuit and packet switching to support the widely varying traffic demands imposed on an integrated network was investigated. The packet switched component is best suited to bursty traffic where some delays in delivery are acceptable. The circuit switched component is reserved for traffic that must meet real time constraints. Selected packet routing algorithms that might be used in an integrated network were simulated. An integrated traffic places widely varying workload demands on a network. Adaptive algorithms were identified, ones that respond to both the transient and evolutionary changes that arise in integrated networks. A new algorithm was developed, hybrid weighted routing, that adapts to workload changes.

The use of artificial neural networks in experimental data acquisition and aerodynamic design

NASA Technical Reports Server (NTRS)

Meade, Andrew J., Jr.

1991-01-01

It is proposed that an artificial neural network be used to construct an intelligent data acquisition system. The artificial neural networks (ANN) model has a potential for replacing traditional procedures as well as for use in computational fluid dynamics validation. Potential advantages of the ANN model are listed. As a proof of concept, the author modeled a NACA 0012 airfoil at specific conditions, using the neural network simulator NETS, developed by James Baffes of the NASA Johnson Space Center. The neural network predictions were compared to the actual data. It is concluded that artificial neural networks can provide an elegant and valuable class of mathematical tools for data analysis.

TranscriptomeBrowser 3.0: introducing a new compendium of molecular interactions and a new visualization tool for the study of gene regulatory networks.

PubMed

Lepoivre, Cyrille; Bergon, Aurélie; Lopez, Fabrice; Perumal, Narayanan B; Nguyen, Catherine; Imbert, Jean; Puthier, Denis

2012-01-31

Deciphering gene regulatory networks by in silico approaches is a crucial step in the study of the molecular perturbations that occur in diseases. The development of regulatory maps is a tedious process requiring the comprehensive integration of various evidences scattered over biological databases. Thus, the research community would greatly benefit from having a unified database storing known and predicted molecular interactions. Furthermore, given the intrinsic complexity of the data, the development of new tools offering integrated and meaningful visualizations of molecular interactions is necessary to help users drawing new hypotheses without being overwhelmed by the density of the subsequent graph. We extend the previously developed TranscriptomeBrowser database with a set of tables containing 1,594,978 human and mouse molecular interactions. The database includes: (i) predicted regulatory interactions (computed by scanning vertebrate alignments with a set of 1,213 position weight matrices), (ii) potential regulatory interactions inferred from systematic analysis of ChIP-seq experiments, (iii) regulatory interactions curated from the literature, (iv) predicted post-transcriptional regulation by micro-RNA, (v) protein kinase-substrate interactions and (vi) physical protein-protein interactions. In order to easily retrieve and efficiently analyze these interactions, we developed In-teractomeBrowser, a graph-based knowledge browser that comes as a plug-in for Transcriptome-Browser. The first objective of InteractomeBrowser is to provide a user-friendly tool to get new insight into any gene list by providing a context-specific display of putative regulatory and physical interactions. To achieve this, InteractomeBrowser relies on a "cell compartments-based layout" that makes use of a subset of the Gene Ontology to map gene products onto relevant cell compartments. This layout is particularly powerful for visual integration of heterogeneous biological information and is a productive avenue in generating new hypotheses. The second objective of InteractomeBrowser is to fill the gap between interaction databases and dynamic modeling. It is thus compatible with the network analysis software Cytoscape and with the Gene Interaction Network simulation software (GINsim). We provide examples underlying the benefits of this visualization tool for large gene set analysis related to thymocyte differentiation. The InteractomeBrowser plugin is a powerful tool to get quick access to a knowledge database that includes both predicted and validated molecular interactions. InteractomeBrowser is available through the TranscriptomeBrowser framework and can be found at: http://tagc.univ-mrs.fr/tbrowser/. Our database is updated on a regular basis.

Analysis of the microRNA signature in left atrium from patients with valvular heart disease reveals their implications in atrial fibrillation.

PubMed

Doñate Puertas, Rosa; Jalabert, Audrey; Meugnier, Emmanuelle; Euthine, Vanessa; Chevalier, Philippe; Rome, Sophie

2018-01-01

Among the potential factors which may contribute to the development and perpetuation of atrial fibrillation, dysregulation of miRNAs has been suggested. Thus in this study, we have quantified the basal expressions of 662 mature human miRNAs in left atrium (LA) from patients undergoing cardiac surgery for valve repair, suffering or not from atrial fibrillation (AF) by using TaqMan® Low Density arrays (v2.0). Among the 299 miRNAs expressed in all patients, 42 miRNAs had altered basal expressions in patients with AF. Binding-site predictions with Targetscan (conserved sites among species) indicated that the up- and down-regulated miRNAs controlled respectively 3,310 and 5,868 genes. To identify the most relevant cellular functions under the control of the altered miRNAs, we focused on the 100 most targeted genes of each list and identified 5 functional protein-protein networks among these genes. Up-regulated networks were involved in synchronisation of circadian rythmicity and in the control of the AKT/PKC signaling pathway (i.e., proliferation/adhesion). Down-regulated networks were the IGF-1 pathway and TGF-beta signaling pathway and a network involved in RNA-mediated gene silencing, suggesting for the first time that alteration of miRNAs in AF would also perturbate the whole miRNA machinery. Then we crossed the list of miRNA predicted genes, and the list of mRNAs altered in similar patients suffering from AF and we found that respectively 44.5% and 55% of the up- and down-regulated mRNA are predicted to be conserved targets of the altered miRNAs (at least one binding site in 3'-UTR). As they were involved in the same biological processes mentioned above, these data demonstrated that a great part of the transcriptional defects previously published in LA from AF patients are likely due to defects at the post-transcriptional level and involved the miRNAs. Our stringent analysis permitted us to identify highly targeted protein-protein networks under the control of miRNAs in LA and, among them, to highlight those specifically affected in AF patients with altered miRNA signature. Further studies are now required to determine whether alterations of miRNA levels in AF pathology are causal or represent an adaptation to prevent cardiac electrical and structural remodeling.

Gene network analysis shows immune-signaling and ERK1/2 as novel genetic markers for multiple addiction phenotypes: alcohol, smoking and opioid addiction.

PubMed

Reyes-Gibby, Cielito C; Yuan, Christine; Wang, Jian; Yeung, Sai-Ching J; Shete, Sanjay

2015-06-05

Addictions to alcohol and tobacco, known risk factors for cancer, are complex heritable disorders. Addictive behaviors have a bidirectional relationship with pain. We hypothesize that the associations between alcohol, smoking, and opioid addiction observed in cancer patients have a genetic basis. Therefore, using bioinformatics tools, we explored the underlying genetic basis and identified new candidate genes and common biological pathways for smoking, alcohol, and opioid addiction. Literature search showed 56 genes associated with alcohol, smoking and opioid addiction. Using Core Analysis function in Ingenuity Pathway Analysis software, we found that ERK1/2 was strongly interconnected across all three addiction networks. Genes involved in immune signaling pathways were shown across all three networks. Connect function from IPA My Pathway toolbox showed that DRD2 is the gene common to both the list of genetic variations associated with all three addiction phenotypes and the components of the brain neuronal signaling network involved in substance addiction. The top canonical pathways associated with the 56 genes were: 1) calcium signaling, 2) GPCR signaling, 3) cAMP-mediated signaling, 4) GABA receptor signaling, and 5) G-alpha i signaling. Cancer patients are often prescribed opioids for cancer pain thus increasing their risk for opioid abuse and addiction. Our findings provide candidate genes and biological pathways underlying addiction phenotypes, which may be future targets for treatment of addiction. Further study of the variations of the candidate genes could allow physicians to make more informed decisions when treating cancer pain with opioid analgesics.

78 FR 47712 - Food and Drug Administration Modernization Act of 1997: Modifications to the List of Recognized...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-08-06

... Application of risk management for IT networks IEC 80001-1 Edition 1.0 2010- incorporating medical devices--Part 1: Roles, 10 responsibilities and activities. 13-39 Application of risk management for IT networks... activities. 13-40 Application of risk management for IT networks IEC/TR 80001-2-1 Edition 1.0 incorporating...

Analysis of MD5 authentication in various routing protocols using simulation tools

NASA Astrophysics Data System (ADS)

Dinakaran, M.; Darshan, K. N.; Patel, Harsh

2017-11-01

Authentication being an important paradigm of security and Computer Networks require secure paths to make the flow of the data even more secure through some security protocols. So MD-5(Message Digest 5) helps in providing data integrity to the data being sent through it and authentication to the network devices. This paper gives a brief introduction to the MD-5, simulation of the networks by including MD-5 authentication using various routing protocols like OSPF, EIGRP and RIPv2. GNS3 is being used to simulate the scenarios. Analysis of the MD-5 authentication is done in the later sections of the paper.

Integration of heterogeneous molecular networks to unravel gene-regulation in Mycobacterium tuberculosis.

PubMed

van Dam, Jesse C J; Schaap, Peter J; Martins dos Santos, Vitor A P; Suárez-Diez, María

2014-09-26

Different methods have been developed to infer regulatory networks from heterogeneous omics datasets and to construct co-expression networks. Each algorithm produces different networks and efforts have been devoted to automatically integrate them into consensus sets. However each separate set has an intrinsic value that is diluted and partly lost when building a consensus network. Here we present a methodology to generate co-expression networks and, instead of a consensus network, we propose an integration framework where the different networks are kept and analysed with additional tools to efficiently combine the information extracted from each network. We developed a workflow to efficiently analyse information generated by different inference and prediction methods. Our methodology relies on providing the user the means to simultaneously visualise and analyse the coexisting networks generated by different algorithms, heterogeneous datasets, and a suite of analysis tools. As a show case, we have analysed the gene co-expression networks of Mycobacterium tuberculosis generated using over 600 expression experiments. Regarding DNA damage repair, we identified SigC as a key control element, 12 new targets for LexA, an updated LexA binding motif, and a potential mismatch repair system. We expanded the DevR regulon with 27 genes while identifying 9 targets wrongly assigned to this regulon. We discovered 10 new genes linked to zinc uptake and a new regulatory mechanism for ZuR. The use of co-expression networks to perform system level analysis allows the development of custom made methodologies. As show cases we implemented a pipeline to integrate ChIP-seq data and another method to uncover multiple regulatory layers. Our workflow is based on representing the multiple types of information as network representations and presenting these networks in a synchronous framework that allows their simultaneous visualization while keeping specific associations from the different networks. By simultaneously exploring these networks and metadata, we gained insights into regulatory mechanisms in M. tuberculosis that could not be obtained through the separate analysis of each data type.

PAINT: a promoter analysis and interaction network generation tool for gene regulatory network identification.

PubMed

Vadigepalli, Rajanikanth; Chakravarthula, Praveen; Zak, Daniel E; Schwaber, James S; Gonye, Gregory E

2003-01-01

We have developed a bioinformatics tool named PAINT that automates the promoter analysis of a given set of genes for the presence of transcription factor binding sites. Based on coincidence of regulatory sites, this tool produces an interaction matrix that represents a candidate transcriptional regulatory network. This tool currently consists of (1) a database of promoter sequences of known or predicted genes in the Ensembl annotated mouse genome database, (2) various modules that can retrieve and process the promoter sequences for binding sites of known transcription factors, and (3) modules for visualization and analysis of the resulting set of candidate network connections. This information provides a substantially pruned list of genes and transcription factors that can be examined in detail in further experimental studies on gene regulation. Also, the candidate network can be incorporated into network identification methods in the form of constraints on feasible structures in order to render the algorithms tractable for large-scale systems. The tool can also produce output in various formats suitable for use in external visualization and analysis software. In this manuscript, PAINT is demonstrated in two case studies involving analysis of differentially regulated genes chosen from two microarray data sets. The first set is from a neuroblastoma N1E-115 cell differentiation experiment, and the second set is from neuroblastoma N1E-115 cells at different time intervals following exposure to neuropeptide angiotensin II. PAINT is available for use as an agent in BioSPICE simulation and analysis framework (www.biospice.org), and can also be accessed via a WWW interface at www.dbi.tju.edu/dbi/tools/paint/.

IMC/RMC Network Professional Film Collection.

ERIC Educational Resources Information Center

New York State Education Dept., Albany. Special Education Instructional Materials Center.

The compilation is a comprehensive listing of films available from the centers in the Instructional Materials Centers/Regional Media Centers (IMC/RMC) Network. Each IMC/RMC location is given a numerical code in a preliminary listing. These numerical codes are used within the film listing, which is arranged alphabetically according to film titles,…

76 FR 15932 - Endangered and Threatened Species; Proposed Listing of Nine Distinct Population Segments of...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-03-22

... Center for Biological Diversity and Turtle Island Restoration Network to list the ``North Pacific... petitioners (Center for Biological Diversity, Turtle Island Restoration Network, and Oceana) sent a 60-day... received a petition from Center for Biological Diversity and Oceana to list the ``Western North Atlantic...

Implementing a Social Knowledge Networking (SKN) system to enable meaningful use of an EHR medication reconciliation system

PubMed Central

Rangachari, Pavani

2018-01-01

Background Despite the regulatory impetus toward meaningful use of electronic health record (EHR) Medication Reconciliation (MedRec) to prevent medication errors during care transitions, hospital adherence has lagged for one chief reason: low physician engagement, stemming from lack of consensus about which physician is responsible for managing a patient’s medication list. In October 2016, Augusta University received a 2-year grant from the Agency for Healthcare Research and Quality to implement a Social Knowledge Networking (SKN) system for enabling its health system (AU Health) to progress from “limited use” of EHR MedRec technology to “meaningful use.” The hypothesis is that SKN would bring together a diverse group of practitioners, to facilitate tacit knowledge exchange on issues related to EHR MedRec, which in turn is expected to increase practitioners’ engagement in addressing those issues and enable meaningful use of EHR. The specific aims are to examine: 1) user-engagement in the SKN system, and 2) associations between “SKN use” and “meaningful use” of EHR. Methods The 2-year project uses an exploratory mixed-method design and consists of three phases: 1) development; 2) SKN implementation; and 3) analysis. Phase 1, completed in May 2017, sought to identify a comprehensive set of issues related to EHR MedRec from practitioners directly involved in the MedRec process. This process facilitated development of a “Reporting Tool” on issues related to EHR MedRec, which, along with an existing “SKN/Discussion Tool,” was integrated into the EHR at AU Health. Phase 2 (launched in June 2017) involves implementing the EHR-integrated SKN system over a 52-week period in inpatient and outpatient medicine units. Discussion The prospective implementation design is expected to generate context-sensitive strategies for meaningful use and successful implementation of EHR MedRec and thereby make substantial contributions to the patient safety and risk management literature. From a health care policy perspective, if the hypothesis holds, federal vendors could be encouraged to incorporate SKN features into EHR systems. PMID:29618941

MAGIA2: from miRNA and genes expression data integrative analysis to microRNA–transcription factor mixed regulatory circuits (2012 update)

PubMed Central

Bisognin, Andrea; Sales, Gabriele; Coppe, Alessandro; Bortoluzzi, Stefania; Romualdi, Chiara

2012-01-01

MAGIA2 (http://gencomp.bio.unipd.it/magia2) is an update, extension and evolution of the MAGIA web tool. It is dedicated to the integrated analysis of in silico target prediction, microRNA (miRNA) and gene expression data for the reconstruction of post-transcriptional regulatory networks. miRNAs are fundamental post-transcriptional regulators of several key biological and pathological processes. As miRNAs act prevalently through target degradation, their expression profiles are expected to be inversely correlated to those of the target genes. Low specificity of target prediction algorithms makes integration approaches an interesting solution for target prediction refinement. MAGIA2 performs this integrative approach supporting different association measures, multiple organisms and almost all target predictions algorithms. Nevertheless, miRNAs activity should be viewed as part of a more complex scenario where regulatory elements and their interactors generate a highly connected network and where gene expression profiles are the result of different levels of regulation. The updated MAGIA2 tries to dissect this complexity by reconstructing mixed regulatory circuits involving either miRNA or transcription factor (TF) as regulators. Two types of circuits are identified: (i) a TF that regulates both a miRNA and its target and (ii) a miRNA that regulates both a TF and its target. PMID:22618880

LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights

PubMed Central

Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

2016-01-01

Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher’s exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO’s usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher. PMID:26750448

LEGO: a novel method for gene set over-representation analysis by incorporating network-based gene weights.

PubMed

Dong, Xinran; Hao, Yun; Wang, Xiao; Tian, Weidong

2016-01-11

Pathway or gene set over-representation analysis (ORA) has become a routine task in functional genomics studies. However, currently widely used ORA tools employ statistical methods such as Fisher's exact test that reduce a pathway into a list of genes, ignoring the constitutive functional non-equivalent roles of genes and the complex gene-gene interactions. Here, we develop a novel method named LEGO (functional Link Enrichment of Gene Ontology or gene sets) that takes into consideration these two types of information by incorporating network-based gene weights in ORA analysis. In three benchmarks, LEGO achieves better performance than Fisher and three other network-based methods. To further evaluate LEGO's usefulness, we compare LEGO with five gene expression-based and three pathway topology-based methods using a benchmark of 34 disease gene expression datasets compiled by a recent publication, and show that LEGO is among the top-ranked methods in terms of both sensitivity and prioritization for detecting target KEGG pathways. In addition, we develop a cluster-and-filter approach to reduce the redundancy among the enriched gene sets, making the results more interpretable to biologists. Finally, we apply LEGO to two lists of autism genes, and identify relevant gene sets to autism that could not be found by Fisher.

Network-based machine learning and graph theory algorithms for precision oncology.

PubMed

Zhang, Wei; Chien, Jeremy; Yong, Jeongsik; Kuang, Rui

2017-01-01

Network-based analytics plays an increasingly important role in precision oncology. Growing evidence in recent studies suggests that cancer can be better understood through mutated or dysregulated pathways or networks rather than individual mutations and that the efficacy of repositioned drugs can be inferred from disease modules in molecular networks. This article reviews network-based machine learning and graph theory algorithms for integrative analysis of personal genomic data and biomedical knowledge bases to identify tumor-specific molecular mechanisms, candidate targets and repositioned drugs for personalized treatment. The review focuses on the algorithmic design and mathematical formulation of these methods to facilitate applications and implementations of network-based analysis in the practice of precision oncology. We review the methods applied in three scenarios to integrate genomic data and network models in different analysis pipelines, and we examine three categories of network-based approaches for repositioning drugs in drug-disease-gene networks. In addition, we perform a comprehensive subnetwork/pathway analysis of mutations in 31 cancer genome projects in the Cancer Genome Atlas and present a detailed case study on ovarian cancer. Finally, we discuss interesting observations, potential pitfalls and future directions in network-based precision oncology.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Boverhof, Joshua R.; Agawal, Deborah A.; Jackson, Keith R.

Nettest is a secure, real-time network utility. The nettest framework is designed to incorporate existing and new network tests, and be run as a daemon or an interactive process. Requests for network tests are received via a SSL connection or the user interface and are authorized using a ACL list (in the future authorization using Akenti will also be supported). For tests that require coordination between the two ends of the test, Nettest establishes an SSL connection to accomplish this coordination. A test between two remote computers can be requested via the user interlace if the Nettest daemon is runningmore » on both remote machines and the user is authorized. Authorization for the test is through a chain of trust estabtished by the nettest daemons. Nettest is responsible for determining if the test request is authorized, but it does nothing further to secure the test once the test is running. Currently the Nettest framework incorporates lperf-vl.2, a simple ping type test, and a tuned TCP test that uses a given required throughput and ping results to determine the round trip time to set a buffer size (based on the delay bandwidth product) and then performs an iperf TCP throughput test. Additional network test tools can be integrated into the Nettest framework in the future.« less

Specificity of V1-V2 Orientation Networks in the Primate Visual Cortex

PubMed Central

Roe, Anna W.; Ts'o, Daniel Y.

2015-01-01

The computation of texture and shape involves integration of features of various orientations. Orientation networks within V1 tend to involve cells which share similar orientation selectivity. However, emergent properties in V2 require the integration of multiple orientations. We now show that, unlike interactions within V1, V1-V2 orientation interactions are much less synchronized and are not necessarily orientation dependent. We find V1-V2 orientation networks are of two types: a more tightly synchronized, orientation-preserving network and a less synchronized orientation-diverse network. We suggest that such diversity of V1-V2 interactions underlies the spatial and functional integration required for computation of higher order contour and shape in V2. PMID:26314798

Quantitative workflow based on NN for weighting criteria in landfill suitability mapping

NASA Astrophysics Data System (ADS)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Alkhasawneh, Mutasem Sh.; Aziz, Hamidi Abdul

2017-10-01

Our study aims to introduce a new quantitative workflow that integrates neural networks (NNs) and multi criteria decision analysis (MCDA). Existing MCDA workflows reveal a number of drawbacks, because of the reliance on human knowledge in the weighting stage. Thus, new workflow presented to form suitability maps at the regional scale for solid waste planning based on NNs. A feed-forward neural network employed in the workflow. A total of 34 criteria were pre-processed to establish the input dataset for NN modelling. The final learned network used to acquire the weights of the criteria. Accuracies of 95.2% and 93.2% achieved for the training dataset and testing dataset, respectively. The workflow was found to be capable of reducing human interference to generate highly reliable maps. The proposed workflow reveals the applicability of NN in generating landfill suitability maps and the feasibility of integrating them with existing MCDA workflows.

Accelerating list management for MPI.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hemmert, K. Scott; Rodrigues, Arun F.; Underwood, Keith Douglas

2005-07-01

The latency and throughput of MPI messages are critically important to a range of parallel scientific applications. In many modern networks, both of these performance characteristics are largely driven by the performance of a processor on the network interface. Because of the semantics of MPI, this embedded processor is forced to traverse a linked list of posted receives each time a message is received. As this list grows long, the latency of message reception grows and the throughput of MPI messages decreases. This paper presents a novel hardware feature to handle list management functions on a network interface. By movingmore » functions such as list insertion, list traversal, and list deletion to the hardware unit, latencies are decreased by up to 20% in the zero length queue case with dramatic improvements in the presence of long queues. Similarly, the throughput is increased by up to 10% in the zero length queue case and by nearly 100% in the presence queues of 30 messages.« less

Spike-train spectra and network response functions for non-linear integrate-and-fire neurons.

PubMed

Richardson, Magnus J E

2008-11-01

Reduced models have long been used as a tool for the analysis of the complex activity taking place in neurons and their coupled networks. Recent advances in experimental and theoretical techniques have further demonstrated the usefulness of this approach. Despite the often gross simplification of the underlying biophysical properties, reduced models can still present significant difficulties in their analysis, with the majority of exact and perturbative results available only for the leaky integrate-and-fire model. Here an elementary numerical scheme is demonstrated which can be used to calculate a number of biologically important properties of the general class of non-linear integrate-and-fire models. Exact results for the first-passage-time density and spike-train spectrum are derived, as well as the linear response properties and emergent states of recurrent networks. Given that the exponential integrate-fire model has recently been shown to agree closely with the experimentally measured response of pyramidal cells, the methodology presented here promises to provide a convenient tool to facilitate the analysis of cortical-network dynamics.

Four Commandments for Writing Policies for Public-Access Wireless Networks

ERIC Educational Resources Information Center

Sauers, Michael

2006-01-01

In this article, the author describes what components should be included in a comprehensive policy for public wireless usage in a library. He lists four basic steps, which include: (1) Introduce the service; (2) List the technical requirements; (3) Spell out disclaimers on access, assistance, and liability; and (4) Alert users to security concerns.

Post-transplant survival in idiopathic pulmonary fibrosis patients concurrently listed for single and double lung transplantation.

PubMed

Chauhan, Dhaval; Karanam, Ashwin B; Merlo, Aurelie; Tom Bozzay, P A; Zucker, Mark J; Seethamraju, Harish; Shariati, Nazly; Russo, Mark J

2016-05-01

Lung transplantation is a widely accepted treatment for patients with end-stage lung disease related to idiopathic pulmonary fibrosis (IPF). However, there are conflicting data on whether double lung transplant (DLT) or single lung transplant (SLT) is the superior therapy in these patients. The purpose of this study was to determine whether actuarial post-transplant graft survival among IPF patients concurrently listed for DLT and SLT is greater for recipients undergoing the former or the latter. The United Network for Organ Sharing provided de-identified patient-level data. Analysis included lung transplant candidates with IPF listed between January 1, 2001 and December 31, 2009 (n = 3,411). The study population included 1,001 (29.3%) lung transplant recipients concurrently listed for DLT and SLT, all ≥18 years of age. The primary outcome measure was actuarial post-transplant graft survival, expressed in years. Among the study population, 433 (43.26%) recipients underwent SLT and 568 (56.74%) recipients underwent DLT. The analysis included 2,722.5 years at risk, with median graft survival of 5.31 years. On univariate (p = 0.317) and multivariate (p = 0.415) regression analyses, there was no difference in graft survival between DLT and SLT. Among IPF recipients concurrently listed for DLT and SLT, there is no statistical difference in actuarial graft survival between recipients undergoing DLT vs SLT. This analysis suggests that increased use of SLT for IPF patients may increase the availability of organs to other candidates, and thus increase the net benefit of these organs, without measurably compromising outcomes. Copyright © 2016 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

Computer-aided-engineering system for modeling and analysis of ECLSS integration testing

NASA Technical Reports Server (NTRS)

Sepahban, Sonbol

1987-01-01

The accurate modeling and analysis of two-phase fluid networks found in environmental control and life support systems is presently undertaken by computer-aided engineering (CAE) techniques whose generalized fluid dynamics package can solve arbitrary flow networks. The CAE system for integrated test bed modeling and analysis will also furnish interfaces and subsystem/test-article mathematical models. Three-dimensional diagrams of the test bed are generated by the system after performing the requisite simulation and analysis.

Location and Size Planning of Distributed Photovoltaic Generation in Distribution network System Based on K-means Clustering Analysis

NASA Astrophysics Data System (ADS)

Lu, Siqi; Wang, Xiaorong; Wu, Junyong

2018-01-01

The paper presents a method to generate the planning scenarios, which is based on K-means clustering analysis algorithm driven by data, for the location and size planning of distributed photovoltaic (PV) units in the network. Taken the power losses of the network, the installation and maintenance costs of distributed PV, the profit of distributed PV and the voltage offset as objectives and the locations and sizes of distributed PV as decision variables, Pareto optimal front is obtained through the self-adaptive genetic algorithm (GA) and solutions are ranked by a method called technique for order preference by similarity to an ideal solution (TOPSIS). Finally, select the planning schemes at the top of the ranking list based on different planning emphasis after the analysis in detail. The proposed method is applied to a 10-kV distribution network in Gansu Province, China and the results are discussed.

Study on Network Error Analysis and Locating based on Integrated Information Decision System

NASA Astrophysics Data System (ADS)

Yang, F.; Dong, Z. H.

2017-10-01

Integrated information decision system (IIDS) integrates multiple sub-system developed by many facilities, including almost hundred kinds of software, which provides with various services, such as email, short messages, drawing and sharing. Because the under-layer protocols are different, user standards are not unified, many errors are occurred during the stages of setup, configuration, and operation, which seriously affect the usage. Because the errors are various, which may be happened in different operation phases, stages, TCP/IP communication protocol layers, sub-system software, it is necessary to design a network error analysis and locating tool for IIDS to solve the above problems. This paper studies on network error analysis and locating based on IIDS, which provides strong theory and technology supports for the running and communicating of IIDS.

BiNA: A Visual Analytics Tool for Biological Network Data

PubMed Central

Gerasch, Andreas; Faber, Daniel; Küntzer, Jan; Niermann, Peter; Kohlbacher, Oliver; Lenhof, Hans-Peter; Kaufmann, Michael

2014-01-01

Interactive visual analysis of biological high-throughput data in the context of the underlying networks is an essential task in modern biomedicine with applications ranging from metabolic engineering to personalized medicine. The complexity and heterogeneity of data sets require flexible software architectures for data analysis. Concise and easily readable graphical representation of data and interactive navigation of large data sets are essential in this context. We present BiNA - the Biological Network Analyzer - a flexible open-source software for analyzing and visualizing biological networks. Highly configurable visualization styles for regulatory and metabolic network data offer sophisticated drawings and intuitive navigation and exploration techniques using hierarchical graph concepts. The generic projection and analysis framework provides powerful functionalities for visual analyses of high-throughput omics data in the context of networks, in particular for the differential analysis and the analysis of time series data. A direct interface to an underlying data warehouse provides fast access to a wide range of semantically integrated biological network databases. A plugin system allows simple customization and integration of new analysis algorithms or visual representations. BiNA is available under the 3-clause BSD license at http://bina.unipax.info/. PMID:24551056

MAS Bulletin. Papers Presented at Advisory Group for Aerospace Research and Development (AGARD) Symposium on Machine Intelligence for Aerospace Electronic Systems.

DTIC Science & Technology

1991-08-01

neural networks, and machine learning . This list ie not all 9. Future ESM Systems and the Potential for Neural Processing inclusive. This research could...U.S. CAPT James M. Skinner , USAF, Air Force Space Technology 17. Development of Tactical Doecisiont Akid. Center, and Prof. Georg* F. Luger...ntegrat11111ng Macine I~1e900enc Into the Co~pi to Aid t" Pilot 26. Integrated Communications, Navigatlion. Ideintiflocation Avionics Dr. Edward J

Using the OCLC union listing component for a statewide health sciences union list of serials.

PubMed Central

Sutton, L S; Wolfgram, P A

1986-01-01

Union lists of serials are critical to the effective operation of interlibrary loan networks. The Michigan Health Sciences Libraries Association used the OCLC union list component to produce the Michigan Statewide Health Sciences Union List of Serials (MISHULS). MISHULS, which includes the serials holdings of ninety-three hospital health sciences libraries, is a subset of a statewide multi-type union list maintained on OCLC. The rationale for a statewide list and the criteria for choosing vendors are discussed. Typical costs are provided. Funding sources are identified and a unique approach to decentralized input is described. The benefits of resource sharing in a larger, multi-type library network are also explored. PMID:3708192

Using the OCLC union listing component for a statewide health sciences union list of serials.

PubMed

Sutton, L S; Wolfgram, P A

1986-04-01

Union lists of serials are critical to the effective operation of interlibrary loan networks. The Michigan Health Sciences Libraries Association used the OCLC union list component to produce the Michigan Statewide Health Sciences Union List of Serials (MISHULS). MISHULS, which includes the serials holdings of ninety-three hospital health sciences libraries, is a subset of a statewide multi-type union list maintained on OCLC. The rationale for a statewide list and the criteria for choosing vendors are discussed. Typical costs are provided. Funding sources are identified and a unique approach to decentralized input is described. The benefits of resource sharing in a larger, multi-type library network are also explored.

Integrating the Medical Home into the EHDI Process

ERIC Educational Resources Information Center

Munoz, Karen F.; Nelson, Lauri; Bradham, Tamala S.; Hoffman, Jeff; Houston, K. Todd

2011-01-01

State coordinators of early hearing detection and intervention (EHDI) programs completed a strengths, weaknesses, opportunities, and threats, or SWOT, analysis that examined 12 areas within state EHDI programs. Related to how the medical home is integrated into the EHDI process, 273 items were listed by 48 coordinators, and themes were identified…

Temporal stability in human interaction networks

NASA Astrophysics Data System (ADS)

Fabbri, Renato; Fabbri, Ricardo; Antunes, Deborah Christina; Pisani, Marilia Mello; de Oliveira, Osvaldo Novais

2017-11-01

This paper reports on stable (or invariant) properties of human interaction networks, with benchmarks derived from public email lists. Activity, recognized through messages sent, along time and topology were observed in snapshots in a timeline, and at different scales. Our analysis shows that activity is practically the same for all networks across timescales ranging from seconds to months. The principal components of the participants in the topological metrics space remain practically unchanged as different sets of messages are considered. The activity of participants follows the expected scale-free trace, thus yielding the hub, intermediary and peripheral classes of vertices by comparison against the Erdös-Rényi model. The relative sizes of these three sectors are essentially the same for all email lists and the same along time. Typically, < 15% of the vertices are hubs, 15%-45% are intermediary and > 45% are peripheral vertices. Similar results for the distribution of participants in the three sectors and for the relative importance of the topological metrics were obtained for 12 additional networks from Facebook, Twitter and ParticipaBR. These properties are consistent with the literature and may be general for human interaction networks, which has important implications for establishing a typology of participants based on quantitative criteria.

Pathways towards instability in financial networks

NASA Astrophysics Data System (ADS)

Caldarelli, Guido; Bardoscia, Marco; Caccioli, Fabio; Battiston, Stefano

There is growing consensus that processes of market integration and risk diversification may come at the price of more systemic risk. Indeed, financial institutions are interconnected in a network of contracts where distress can either be amplified or dampened. However, a mathematical understanding of instability in relation to the network topology is still lacking. In a model financial network, we show that the origin of instability resides in the presence of specific types of cyclical structures, regardless of many of the details of the distress propagation mechanism. In particular, we show the existence of trajectories in the space of graphs along which a complex network turns from stable to unstable, although at each point along the trajectory its nodes satisfy constraints that would apparently make them individually stable. In the financial context, our findings have important implications for policies aimed at increasing financial stability. We illustrate the propositions on a sample dataset for the top 50 EU listed banks between 2008 and 2013. More in general, our results shed light on previous findings on the instability of model ecosystems and are relevant for a broad class of dynamical processes on complex networks.

Structural reliability calculation method based on the dual neural network and direct integration method.

PubMed

Li, Haibin; He, Yun; Nie, Xiaobo

2018-01-01

Structural reliability analysis under uncertainty is paid wide attention by engineers and scholars due to reflecting the structural characteristics and the bearing actual situation. The direct integration method, started from the definition of reliability theory, is easy to be understood, but there are still mathematics difficulties in the calculation of multiple integrals. Therefore, a dual neural network method is proposed for calculating multiple integrals in this paper. Dual neural network consists of two neural networks. The neural network A is used to learn the integrand function, and the neural network B is used to simulate the original function. According to the derivative relationships between the network output and the network input, the neural network B is derived from the neural network A. On this basis, the performance function of normalization is employed in the proposed method to overcome the difficulty of multiple integrations and to improve the accuracy for reliability calculations. The comparisons between the proposed method and Monte Carlo simulation method, Hasofer-Lind method, the mean value first-order second moment method have demonstrated that the proposed method is an efficient and accurate reliability method for structural reliability problems.

Air Pollution Measurements by Citizen Scientists and NASA Satellites: Data Integration and Analysis

NASA Astrophysics Data System (ADS)

Gupta, P.; Maibach, J.; Levy, R. C.; Doraiswamy, P.; Pikelnaya, O.; Feenstra, B.; Polidori, A.

2017-12-01

PM2.5, or fine particulate matter, is a category of air pollutant consisting of solid particles with effective aerodynamic diameter of less than 2.5 microns. These particles are hazardous to human health, as their small size allows them to penetrate deep into the lungs. Since the late 1990's, the US Environmental Protection Agency has been monitoring PM2.5 using a network of ground-level sensors. Due to cost and space restrictions, the EPA monitoring network remains spatially sparse. That is, while the network spans the extent of the US, the distance between sensors is large enough that significant spatial variation in PM concentration can go undetected. To increase the spatial resolution of monitoring, previous studies have used satellite data to estimate ground-level PM concentrations. From imagery, one can create a measure of haziness due to aerosols, called aerosol optical depth (AOD), which then can be used to estimate PM concentrations using statistical and physical modeling. Additionally, previous research has identified a number of meteorological variables, such as relative humidity and mixing height, which aide in estimating PM concentrations from AOD. Although the high spatial resolution of satellite data is valuable alone for forecasting air quality, higher resolution ground-level data is needed to effectively study the relationship between PM2.5 concentrations and AOD. To this end, we discuss a citizen-science PM monitoring network deployed in California. Using low-cost PM sensors, this network achieves higher spatial resolution. We additionally discuss a software pipeline for integrating resulting PM measurements with satellite data, as well as initial data analysis.

Nouvelle methode d'integration energetique pour la retro-installation des procedes industriels et la transformation des usines papetieres

NASA Astrophysics Data System (ADS)

Bonhivers, Jean-Christophe

The increase in production of goods over the last decades has led to the need for improving the management of natural resources management and the efficiency of processes. As a consequence, heat integration methods for industry have been developed. These have been successful for the design of new plants: the integration principles are largely employed, and energy intensity has dramatically decreased in many processes. Although progress has also been achieved in integration methods for retrofit, these methods still need further conceptual development. Furthermore, methodological difficulties increase when trying to retrofit heat exchange networks that are closely interrelated to water networks, such as the case of pulp and paper mills. The pulp and paper industry seeks to increase its profitability by reducing production costs and optimizing supply chains. Recent process developments in forestry biorefining give this industry the opportunity for diversification into bio-products, increasing potential profit margins, and at the same time modernizing its energy systems. Identification of energy strategies for a mill in a changing environment, including the possibility of adding a biorefinery process on the industrial site, requires better integration methods for retrofit situations. The objective of this thesis is to develop an energy integration method for the retrofit of industrial systems and the transformation of pulp and paper mills, ant to demonstrate the method in case studies. Energy is conserved and degraded in a process. Heat can be converted into electricity, stored as chemical energy, or rejected to the environment. A systematic analysis of successive degradations of energy between the hot utilities until the environment, through process operations and existing heat exchangers, is essential in order to reduce the heat consumption. In this thesis, the "Bridge Method" for energy integration by heat exchanger network retrofit has been developed. This method is the first that considers the analysis of these degradations. The fundamental mechanism to reduce the heat consumption in an existing network has been made explicit; it is the basis of the developed method. The Bridge Method includes the definition of "a bridge", which is a set of modifications leading to heat reduction in a heat exchanger network. It is proven that, for a given set of streams, only bridges can lead to heat savings. The Bridge Method also includes (1) a global procedure for heat exchanger network retrofit, (2) a procedure to enumerate systematically the bridges, (3) "a network table" to easily evaluate them, and (4) an "energy transfer diagram" showing the effect of the two first principles of thermodynamics of energy conservation and degradation in industrial processes in order to identify energy savings opportunities. The Bridge Method can be used for the analysis of networks including several types of heat transfer, and site-wide analysis. The Bridge Method has been applied in case studies for retrofitting networks composed of indirect-contact heat exchangers, including the network of a kraft pulp mill, and also networks of direct-contact heat exchangers, including the hot water production system of a pulp mill. The method has finally been applied for the evaluation of a biorefinery process, alone or hosted in a kraft pulp mill. Results show that the use of the method significantly reduces the search space and leads to identification of the relevant solutions. The necessity of a bridge to reduce the inputs and outputs of a process is a consequence of the two first thermodynamics principles of energy conservation and increase in entropy. The concept of bridge alone can also be used as a tool for process analysis, and in numerical optimization-based approaches for energy integration.

U.S. Geological Survey DLG-3 and Bureau of the Census TIGER data. Development and GIS applications

USGS Publications Warehouse

Batten, Lawrence G.

1990-01-01

The U.S. Geological Survey has been actively developing digital cartographic and geographic data and standards since the early 1970's. One product is Digital Line Graph data, which offer a consistently accurate source of base category geographic information. The Bureau of the Census has combined their Dual Independent Map Encoding data with the Geological Survey's 1:100,000-scale Digital Line Graph data to prepare for the 1990 decennial census. The resulting Topologically Integrated Geographic Encoding and Referencing data offer a wealth of information. A major area of research using these data is in transportation analysis. The attributes associated with Digital Line Graphs can be used to determine the average travel times along each segment. Geographic information system functions can then be used to optimize routes through the network and to generate street name lists. Additional aspects of the subject are discussed.

Integrating Biodiversity Data into Botanic Collections

PubMed Central

2016-01-01

Abstract Background Today's species names are entry points into a web of publicly available knowledge and are integral parts of legislation concerning biological conservation and consumer safety. Species information usually is fragmented, can be misleading due to the existence of different names and might even be biased because of an identical name that is used for a different species. Safely navigating through the name space is one of the most challenging tasks when associating names with data and when decisions are made which name to include in legislation. Integrating publicly available dynamic data to characterise plant genetic resources of botanic gardens and other facilities will significantly increase the efficiency of recovering relevant information for research projects, identifying potentially invasive taxa, constructing priority lists and developing DNA-based specimen authentication. New information To demonstrate information availability and discuss integration into botanic collections, scientific names derived from botanic gardens were evaluated using the Encyclopedia of Life, The Catalogue of Life and The Plant List. 98.5% of the names could be verified by the combined use of these providers. Comparing taxonomic status information 13 % of the cases were in disagreement. About 7 % of the verified names were found to be included in the International Union for Conservation of Nature Red List, including one extinct taxon and three taxa with the status "extinct in the wild". As second most important factor for biodiversity loss, potential invasiveness was determined. Approximately 4 % of the verified names were detected using the Global Invasive Species Information Network, including 208 invasive taxa. According to Delivering Alien Invasive Species Inventories for Europe around 20 % of the verified names are European alien taxa including 15 of the worst European invasive taxa. Considering alternative names in the data recovery process, success increased up to 18 %. PMID:27346953

Integrating Biodiversity Data into Botanic Collections.

PubMed

Horn, Thomas

2016-01-01

Today's species names are entry points into a web of publicly available knowledge and are integral parts of legislation concerning biological conservation and consumer safety. Species information usually is fragmented, can be misleading due to the existence of different names and might even be biased because of an identical name that is used for a different species. Safely navigating through the name space is one of the most challenging tasks when associating names with data and when decisions are made which name to include in legislation. Integrating publicly available dynamic data to characterise plant genetic resources of botanic gardens and other facilities will significantly increase the efficiency of recovering relevant information for research projects, identifying potentially invasive taxa, constructing priority lists and developing DNA-based specimen authentication. To demonstrate information availability and discuss integration into botanic collections, scientific names derived from botanic gardens were evaluated using the Encyclopedia of Life, The Catalogue of Life and The Plant List. 98.5% of the names could be verified by the combined use of these providers. Comparing taxonomic status information 13 % of the cases were in disagreement. About 7 % of the verified names were found to be included in the International Union for Conservation of Nature Red List, including one extinct taxon and three taxa with the status "extinct in the wild". As second most important factor for biodiversity loss, potential invasiveness was determined. Approximately 4 % of the verified names were detected using the Global Invasive Species Information Network, including 208 invasive taxa. According to Delivering Alien Invasive Species Inventories for Europe around 20 % of the verified names are European alien taxa including 15 of the worst European invasive taxa. Considering alternative names in the data recovery process, success increased up to 18 %.

Network analysis reveals stage-specific changes in zebrafish embryo development using time course whole transcriptome profiling and prior biological knowledge.

PubMed

Zhang, Yuji

2015-01-01

Molecular networks act as the backbone of molecular activities within cells, offering a unique opportunity to better understand the mechanism of diseases. While network data usually constitute only static network maps, integrating them with time course gene expression information can provide clues to the dynamic features of these networks and unravel the mechanistic driver genes characterizing cellular responses. Time course gene expression data allow us to broadly "watch" the dynamics of the system. However, one challenge in the analysis of such data is to establish and characterize the interplay among genes that are altered at different time points in the context of a biological process or functional category. Integrative analysis of these data sources will lead us a more complete understanding of how biological entities (e.g., genes and proteins) coordinately perform their biological functions in biological systems. In this paper, we introduced a novel network-based approach to extract functional knowledge from time-dependent biological processes at a system level using time course mRNA sequencing data in zebrafish embryo development. The proposed method was applied to investigate 1α, 25(OH)2D3-altered mechanisms in zebrafish embryo development. We applied the proposed method to a public zebrafish time course mRNA-Seq dataset, containing two different treatments along four time points. We constructed networks between gene ontology biological process categories, which were enriched in differential expressed genes between consecutive time points and different conditions. The temporal propagation of 1α, 25-Dihydroxyvitamin D3-altered transcriptional changes started from a few genes that were altered initially at earlier stage, to large groups of biological coherent genes at later stages. The most notable biological processes included neuronal and retinal development and generalized stress response. In addition, we also investigated the relationship among biological processes enriched in co-expressed genes under different conditions. The enriched biological processes include translation elongation, nucleosome assembly, and retina development. These network dynamics provide new insights into the impact of 1α, 25-Dihydroxyvitamin D3 treatment in bone and cartilage development. We developed a network-based approach to analyzing the DEGs at different time points by integrating molecular interactions and gene ontology information. These results demonstrate that the proposed approach can provide insight on the molecular mechanisms taking place in vertebrate embryo development upon treatment with 1α, 25(OH)2D3. Our approach enables the monitoring of biological processes that can serve as a basis for generating new testable hypotheses. Such network-based integration approach can be easily extended to any temporal- or condition-dependent genomic data analyses.

Performance analysis of Integrated Communication and Control System networks

NASA Technical Reports Server (NTRS)

Halevi, Y.; Ray, A.

1990-01-01

This paper presents statistical analysis of delays in Integrated Communication and Control System (ICCS) networks that are based on asynchronous time-division multiplexing. The models are obtained in closed form for analyzing control systems with randomly varying delays. The results of this research are applicable to ICCS design for complex dynamical processes like advanced aircraft and spacecraft, autonomous manufacturing plants, and chemical and processing plants.

Functional Module Analysis for Gene Coexpression Networks with Network Integration.

PubMed

Zhang, Shuqin; Zhao, Hongyu; Ng, Michael K

2015-01-01

Network has been a general tool for studying the complex interactions between different genes, proteins, and other small molecules. Module as a fundamental property of many biological networks has been widely studied and many computational methods have been proposed to identify the modules in an individual network. However, in many cases, a single network is insufficient for module analysis due to the noise in the data or the tuning of parameters when building the biological network. The availability of a large amount of biological networks makes network integration study possible. By integrating such networks, more informative modules for some specific disease can be derived from the networks constructed from different tissues, and consistent factors for different diseases can be inferred. In this paper, we have developed an effective method for module identification from multiple networks under different conditions. The problem is formulated as an optimization model, which combines the module identification in each individual network and alignment of the modules from different networks together. An approximation algorithm based on eigenvector computation is proposed. Our method outperforms the existing methods, especially when the underlying modules in multiple networks are different in simulation studies. We also applied our method to two groups of gene coexpression networks for humans, which include one for three different cancers, and one for three tissues from the morbidly obese patients. We identified 13 modules with three complete subgraphs, and 11 modules with two complete subgraphs, respectively. The modules were validated through Gene Ontology enrichment and KEGG pathway enrichment analysis. We also showed that the main functions of most modules for the corresponding disease have been addressed by other researchers, which may provide the theoretical basis for further studying the modules experimentally.

Rapid processing of PET list-mode data for efficient uncertainty estimation and data analysis

NASA Astrophysics Data System (ADS)

Markiewicz, P. J.; Thielemans, K.; Schott, J. M.; Atkinson, D.; Arridge, S. R.; Hutton, B. F.; Ourselin, S.

2016-07-01

In this technical note we propose a rapid and scalable software solution for the processing of PET list-mode data, which allows the efficient integration of list mode data processing into the workflow of image reconstruction and analysis. All processing is performed on the graphics processing unit (GPU), making use of streamed and concurrent kernel execution together with data transfers between disk and CPU memory as well as CPU and GPU memory. This approach leads to fast generation of multiple bootstrap realisations, and when combined with fast image reconstruction and analysis, it enables assessment of uncertainties of any image statistic and of any component of the image generation process (e.g. random correction, image processing) within reasonable time frames (e.g. within five minutes per realisation). This is of particular value when handling complex chains of image generation and processing. The software outputs the following: (1) estimate of expected random event data for noise reduction; (2) dynamic prompt and random sinograms of span-1 and span-11 and (3) variance estimates based on multiple bootstrap realisations of (1) and (2) assuming reasonable count levels for acceptable accuracy. In addition, the software produces statistics and visualisations for immediate quality control and crude motion detection, such as: (1) count rate curves; (2) centre of mass plots of the radiodistribution for motion detection; (3) video of dynamic projection views for fast visual list-mode skimming and inspection; (4) full normalisation factor sinograms. To demonstrate the software, we present an example of the above processing for fast uncertainty estimation of regional SUVR (standard uptake value ratio) calculation for a single PET scan of 18F-florbetapir using the Siemens Biograph mMR scanner.

Early Experiences with Mobile Electronic Health Records Application in a Tertiary Hospital in Korea

PubMed Central

Park, Minah; Hong, Eunseok; Kim, Sunhyu; Ahn, Ryeok; Hong, Jungseok; Song, Seungyeol; Kim, Tak; Kim, Jeongkeun; Yeo, Seongwoon

2015-01-01

Objectives Recent advances in mobile technology have opened up possibilities to provide strongly integrated mobile-based services in healthcare and telemedicine. Although the number of mobile Electronic Health Record (EHR) applications is large and growing, there is a paucity of evidence demonstrating the usage patterns of these mobile applications by healthcare providers. This study aimed to illustrate the deployment process for an integrated mobile EHR application and to analyze usage patterns after provision of the mobile EHR service. Methods We developed an integrated mobile application that aimed to enhance the mobility of healthcare providers by improving access to patient- and hospital-related information during their daily medical activities. The study included mobile EHR users who accessed patient healthcare records between May 2013 and May 2014. We performed a data analysis using a web server log file analyzer from the integrated EHR system. Cluster analysis was applied to longitudinal user data based on their application usage pattern. Results The mobile EHR service named M-UMIS has been in service since May 2013. Every healthcare provider in the hospital could access the mobile EHR service and view the medical charts of their patients. The frequency of using services and network packet transmission on the M-UMIS increased gradually during the study period. The most frequently accessed service in the menu was the patient list. Conclusions A better understanding regarding the adoption of mobile EHR applications by healthcare providers in patient-centered care provides useful information to guide the design and implementation of future applications. PMID:26618036

Consensus strategy in genes prioritization and combined bioinformatics analysis for preeclampsia pathogenesis.

PubMed

Tejera, Eduardo; Cruz-Monteagudo, Maykel; Burgos, Germán; Sánchez, María-Eugenia; Sánchez-Rodríguez, Aminael; Pérez-Castillo, Yunierkis; Borges, Fernanda; Cordeiro, Maria Natália Dias Soeiro; Paz-Y-Miño, César; Rebelo, Irene

2017-08-08

Preeclampsia is a multifactorial disease with unknown pathogenesis. Even when recent studies explored this disease using several bioinformatics tools, the main objective was not directed to pathogenesis. Additionally, consensus prioritization was proved to be highly efficient in the recognition of genes-disease association. However, not information is available about the consensus ability to early recognize genes directly involved in pathogenesis. Therefore our aim in this study is to apply several theoretical approaches to explore preeclampsia; specifically those genes directly involved in the pathogenesis. We firstly evaluated the consensus between 12 prioritization strategies to early recognize pathogenic genes related to preeclampsia. A communality analysis in the protein-protein interaction network of previously selected genes was done including further enrichment analysis. The enrichment analysis includes metabolic pathways as well as gene ontology. Microarray data was also collected and used in order to confirm our results or as a strategy to weight the previously enriched pathways. The consensus prioritized gene list was rationally filtered to 476 genes using several criteria. The communality analysis showed an enrichment of communities connected with VEGF-signaling pathway. This pathway is also enriched considering the microarray data. Our result point to VEGF, FLT1 and KDR as relevant pathogenic genes, as well as those connected with NO metabolism. Our results revealed that consensus strategy improve the detection and initial enrichment of pathogenic genes, at least in preeclampsia condition. Moreover the combination of the first percent of the prioritized genes with protein-protein interaction network followed by communality analysis reduces the gene space. This approach actually identifies well known genes related with pathogenesis. However, genes like HSP90, PAK2, CD247 and others included in the first 1% of the prioritized list need to be further explored in preeclampsia pathogenesis through experimental approaches.

A study of structural properties of gene network graphs for mathematical modeling of integrated mosaic gene networks.

PubMed

Petrovskaya, Olga V; Petrovskiy, Evgeny D; Lavrik, Inna N; Ivanisenko, Vladimir A

2017-04-01

Gene network modeling is one of the widely used approaches in systems biology. It allows for the study of complex genetic systems function, including so-called mosaic gene networks, which consist of functionally interacting subnetworks. We conducted a study of a mosaic gene networks modeling method based on integration of models of gene subnetworks by linear control functionals. An automatic modeling of 10,000 synthetic mosaic gene regulatory networks was carried out using computer experiments on gene knockdowns/knockouts. Structural analysis of graphs of generated mosaic gene regulatory networks has revealed that the most important factor for building accurate integrated mathematical models, among those analyzed in the study, is data on expression of genes corresponding to the vertices with high properties of centrality.

Graph theory network function in Parkinson's disease assessed with electroencephalography.

PubMed

Utianski, Rene L; Caviness, John N; van Straaten, Elisabeth C W; Beach, Thomas G; Dugger, Brittany N; Shill, Holly A; Driver-Dunckley, Erika D; Sabbagh, Marwan N; Mehta, Shyamal; Adler, Charles H; Hentz, Joseph G

2016-05-01

To determine what differences exist in graph theory network measures derived from electroencephalography (EEG), between Parkinson's disease (PD) patients who are cognitively normal (PD-CN) and matched healthy controls; and between PD-CN and PD dementia (PD-D). EEG recordings were analyzed via graph theory network analysis to quantify changes in global efficiency and local integration. This included minimal spanning tree analysis. T-tests and correlations were used to assess differences between groups and assess the relationship with cognitive performance. Network measures showed increased local integration across all frequency bands between control and PD-CN; in contrast, decreased local integration occurred in PD-D when compared to PD-CN in the alpha1 frequency band. Differences found in PD-MCI mirrored PD-D. Correlations were found between network measures and assessments of global cognitive performance in PD. Our results reveal distinct patterns of band and network measure type alteration and breakdown for PD, as well as with cognitive decline in PD. These patterns suggest specific ways that interaction between cortical areas becomes abnormal and contributes to PD symptoms at various stages. Graph theory analysis by EEG suggests that network alteration and breakdown are robust attributes of PD cortical dysfunction pathophysiology. Copyright © 2016 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Implementation of Integrated Service Networks under the Quebec Mental Health Reform: Facilitators and Barriers associated with Different Territorial Profiles.

PubMed

Fleury, Marie-Josée; Grenier, Guy; Vallée, Catherine; Aubé, Denise; Farand, Lambert

2017-03-10

This study evaluates implementation of the Quebec Mental Health Reform (2005-2015), which promoted the development of integrated service networks, in 11 local service networks organized into four territorial groups according to socio-demographic characteristics and mental health services offered. Data were collected from documents concerning networks; structured questionnaires completed by 90 managers and by 16 respondent-psychiatrists; and semi-structured interviews with 102 network stakeholders. Factors associated with implementation and integration were organized according to: 1) reform characteristics; 2) implementation context; 3) organizational characteristics; and 4) integration strategies. While local networks were in a process of development and expansion, none were fully integrated at the time of the study. Facilitators and barriers to implementation and integration were primarily associated with organizational characteristics. Integration was best achieved in larger networks including a general hospital with a psychiatric department, followed by networks with a psychiatric hospital. Formalized integration strategies such as service agreements, liaison officers, and joint training reduced some barriers to implementation in networks experiencing less favourable conditions. Strategies for the implementation of healthcare reform and integrated service networks should include sustained support and training in best-practices, adequate performance indicators and resources, formalized integration strategies to improve network coordination and suitable initiatives to promote staff retention.

Structural analysis of health-relevant policy-making information exchange networks in Canada.

PubMed

Contandriopoulos, Damien; Benoît, François; Bryant-Lukosius, Denise; Carrier, Annie; Carter, Nancy; Deber, Raisa; Duhoux, Arnaud; Greenhalgh, Trisha; Larouche, Catherine; Leclerc, Bernard-Simon; Levy, Adrian; Martin-Misener, Ruth; Maximova, Katerina; McGrail, Kimberlyn; Nykiforuk, Candace; Roos, Noralou; Schwartz, Robert; Valente, Thomas W; Wong, Sabrina; Lindquist, Evert; Pullen, Carolyn; Lardeux, Anne; Perroux, Melanie

2017-09-20

Health systems worldwide struggle to identify, adopt, and implement in a timely and system-wide manner the best-evidence-informed-policy-level practices. Yet, there is still only limited evidence about individual and institutional best practices for fostering the use of scientific evidence in policy-making processes The present project is the first national-level attempt to (1) map and structurally analyze-quantitatively-health-relevant policy-making networks that connect evidence production, synthesis, interpretation, and use; (2) qualitatively investigate the interaction patterns of a subsample of actors with high centrality metrics within these networks to develop an in-depth understanding of evidence circulation processes; and (3) combine these findings in order to assess a policy network's "absorptive capacity" regarding scientific evidence and integrate them into a conceptually sound and empirically grounded framework. The project is divided into two research components. The first component is based on quantitative analysis of ties (relationships) that link nodes (participants) in a network. Network data will be collected through a multi-step snowball sampling strategy. Data will be analyzed structurally using social network mapping and analysis methods. The second component is based on qualitative interviews with a subsample of the Web survey participants having central, bridging, or atypical positions in the network. Interviews will focus on the process through which evidence circulates and enters practice. Results from both components will then be integrated through an assessment of the network's and subnetwork's effectiveness in identifying, capturing, interpreting, sharing, reframing, and recodifying scientific evidence in policy-making processes. Knowledge developed from this project has the potential both to strengthen the scientific understanding of how policy-level knowledge transfer and exchange functions and to provide significantly improved advice on how to ensure evidence plays a more prominent role in public policies.

Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments

PubMed Central

Canales, Javier; Moyano, Tomás C.; Villarroel, Eva; Gutiérrez, Rodrigo A.

2014-01-01

Nitrogen (N) is an essential macronutrient for plant growth and development. Plants adapt to changes in N availability partly by changes in global gene expression. We integrated publicly available root microarray data under contrasting nitrate conditions to identify new genes and functions important for adaptive nitrate responses in Arabidopsis thaliana roots. Overall, more than 2000 genes exhibited changes in expression in response to nitrate treatments in Arabidopsis thaliana root organs. Global regulation of gene expression by nitrate depends largely on the experimental context. However, despite significant differences from experiment to experiment in the identity of regulated genes, there is a robust nitrate response of specific biological functions. Integrative gene network analysis uncovered relationships between nitrate-responsive genes and 11 highly co-expressed gene clusters (modules). Four of these gene network modules have robust nitrate responsive functions such as transport, signaling, and metabolism. Network analysis hypothesized G2-like transcription factors are key regulatory factors controlling transport and signaling functions. Our meta-analysis highlights the role of biological processes not studied before in the context of the nitrate response such as root hair development and provides testable hypothesis to advance our understanding of nitrate responses in plants. PMID:24570678

Integrated molecular portrait of non-small cell lung cancers

PubMed Central

2013-01-01

Background Non-small cell lung cancer (NSCLC), a leading cause of cancer deaths, represents a heterogeneous group of neoplasms, mostly comprising squamous cell carcinoma (SCC), adenocarcinoma (AC) and large-cell carcinoma (LCC). The objectives of this study were to utilize integrated genomic data including copy-number alteration, mRNA, microRNA expression and candidate-gene full sequencing data to characterize the molecular distinctions between AC and SCC. Methods Comparative genomic hybridization followed by mutational analysis, gene expression and miRNA microarray profiling were performed on 123 paired tumor and non-tumor tissue samples from patients with NSCLC. Results At DNA, mRNA and miRNA levels we could identify molecular markers that discriminated significantly between the various histopathological entities of NSCLC. We identified 34 genomic clusters using aCGH data; several genes exhibited a different profile of aberrations between AC and SCC, including PIK3CA, SOX2, THPO, TP63, PDGFB genes. Gene expression profiling analysis identified SPP1, CTHRC1and GREM1 as potential biomarkers for early diagnosis of the cancer, and SPINK1 and BMP7 to distinguish between AC and SCC in small biopsies or in blood samples. Using integrated genomics approach we found in recurrently altered regions a list of three potential driver genes, MRPS22, NDRG1 and RNF7, which were consistently over-expressed in amplified regions, had wide-spread correlation with an average of ~800 genes throughout the genome and highly associated with histological types. Using a network enrichment analysis, the targets of these potential drivers were seen to be involved in DNA replication, cell cycle, mismatch repair, p53 signalling pathway and other lung cancer related signalling pathways, and many immunological pathways. Furthermore, we also identified one potential driver miRNA hsa-miR-944. Conclusions Integrated molecular characterization of AC and SCC helped identify clinically relevant markers and potential drivers, which are recurrent and stable changes at DNA level that have functional implications at RNA level and have strong association with histological subtypes. PMID:24299561

Atypical language laterality is associated with large-scale disruption of network integration in children with intractable focal epilepsy.

PubMed

Ibrahim, George M; Morgan, Benjamin R; Doesburg, Sam M; Taylor, Margot J; Pang, Elizabeth W; Donner, Elizabeth; Go, Cristina Y; Rutka, James T; Snead, O Carter

2015-04-01

Epilepsy is associated with disruption of integration in distributed networks, together with altered localization for functions such as expressive language. The relation between atypical network connectivity and altered localization is unknown. In the current study we tested whether atypical expressive language laterality was associated with the alteration of large-scale network integration in children with medically-intractable localization-related epilepsy (LRE). Twenty-three right-handed children (age range 8-17) with medically-intractable LRE performed a verb generation task in fMRI. Language network activation was identified and the Laterality index (LI) was calculated within the pars triangularis and pars opercularis. Resting-state data from the same cohort were subjected to independent component analysis. Dual regression was used to identify associations between resting-state integration and LI values. Higher positive values of the LI, indicating typical language localization were associated with stronger functional integration of various networks including the default mode network (DMN). The normally symmetric resting-state networks showed a pattern of lateralized connectivity mirroring that of language function. The association between atypical language localization and network integration implies a widespread disruption of neural network development. These findings may inform the interpretation of localization studies by providing novel insights into reorganization of neural networks in epilepsy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Comprehensive Analysis of Gene Expression Profiles of Sepsis-Induced Multiorgan Failure Identified Its Valuable Biomarkers.

PubMed

Wang, Yumei; Yin, Xiaoling; Yang, Fang

2018-02-01

Sepsis is an inflammatory-related disease, and severe sepsis would induce multiorgan dysfunction, which is the most common cause of death of patients in noncoronary intensive care units. Progression of novel therapeutic strategies has proven to be of little impact on the mortality of severe sepsis, and unfortunately, its mechanisms still remain poorly understood. In this study, we analyzed gene expression profiles of severe sepsis with failure of lung, kidney, and liver for the identification of potential biomarkers. We first downloaded the gene expression profiles from the Gene Expression Omnibus and performed preprocessing of raw microarray data sets and identification of differential expression genes (DEGs) through the R programming software; then, significantly enriched functions of DEGs in lung, kidney, and liver failure sepsis samples were obtained from the Database for Annotation, Visualization, and Integrated Discovery; finally, protein-protein interaction network was constructed for DEGs based on the STRING database, and network modules were also obtained through the MCODE cluster method. As a result, lung failure sepsis has the highest number of DEGs of 859, whereas the number of DEGs in kidney and liver failure sepsis samples is 178 and 175, respectively. In addition, 17 overlaps were obtained among the three lists of DEGs. Biological processes related to immune and inflammatory response were found to be significantly enriched in DEGs. Network and module analysis identified four gene clusters in which all or most of genes were upregulated. The expression changes of Icam1 and Socs3 were further validated through quantitative PCR analysis. This study should shed light on the development of sepsis and provide potential therapeutic targets for sepsis-induced multiorgan failure.

A Net of Friends: Investigating Friendship by Integrating Attachment Theory and Social Network Analysis.

PubMed

Gillath, Omri; Karantzas, Gery C; Selcuk, Emre

2017-11-01

The current article focuses on attachment style-an individual difference widely studied in the field of close relationships-and its application to the study of social networks. Specifically, we investigated whether attachment style predicts perception and management of social networks. In Study 1, we examined the associations of attachment style with perceptions of network tie strength and multiplexity. In Studies 2a and 2b, we investigated the association between attachment style and network management skills (initiating, maintaining, and dissolving ties) and whether network management skills mediated the associations of attachment style with network tie strength and multiplexity. In Study 3, experimentally enhancing attachment security made people more likely to initiate and less likely to dissolve social ties (for the latter, especially among those high on avoidance or anxiety). As for maintenance, security priming also increased maintenance; however, mainly among people high on attachment anxiety or low on attachment avoidance.

Genomics Portals: integrative web-platform for mining genomics data.

PubMed

Shinde, Kaustubh; Phatak, Mukta; Johannes, Freudenberg M; Chen, Jing; Li, Qian; Vineet, Joshi K; Hu, Zhen; Ghosh, Krishnendu; Meller, Jaroslaw; Medvedovic, Mario

2010-01-13

A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org.

Genomics Portals: integrative web-platform for mining genomics data

PubMed Central

2010-01-01

Background A large amount of experimental data generated by modern high-throughput technologies is available through various public repositories. Our knowledge about molecular interaction networks, functional biological pathways and transcriptional regulatory modules is rapidly expanding, and is being organized in lists of functionally related genes. Jointly, these two sources of information hold a tremendous potential for gaining new insights into functioning of living systems. Results Genomics Portals platform integrates access to an extensive knowledge base and a large database of human, mouse, and rat genomics data with basic analytical visualization tools. It provides the context for analyzing and interpreting new experimental data and the tool for effective mining of a large number of publicly available genomics datasets stored in the back-end databases. The uniqueness of this platform lies in the volume and the diversity of genomics data that can be accessed and analyzed (gene expression, ChIP-chip, ChIP-seq, epigenomics, computationally predicted binding sites, etc), and the integration with an extensive knowledge base that can be used in such analysis. Conclusion The integrated access to primary genomics data, functional knowledge and analytical tools makes Genomics Portals platform a unique tool for interpreting results of new genomics experiments and for mining the vast amount of data stored in the Genomics Portals backend databases. Genomics Portals can be accessed and used freely at http://GenomicsPortals.org. PMID:20070909

The influence of management and environment on local health department organizational structure and adaptation: a longitudinal network analysis.

PubMed

Keeling, Jonathan W; Pryde, Julie A; Merrill, Jacqueline A

2013-01-01

The nation's 2862 local health departments (LHDs) are the primary means for assuring public health services for all populations. The objective of this study is to assess the effect of organizational network analysis on management decisions in LHDs and to demonstrate the technique's ability to detect organizational adaptation over time. We conducted a longitudinal network analysis in a full-service LHD with 113 employees serving about 187,000 persons. Network survey data were collected from employees at 3 times: months 0, 8, and 34. At time 1 the initial analysis was presented to LHD managers as an intervention with information on evidence-based management strategies to address the findings. At times 2 and 3 interviews documented managers' decision making and events in the task environment. Response rates for the 3 network analyses were 90%, 97%, and 83%. Postintervention (time 2) results showed beneficial changes in network measures of communication and integration. Screening and case identification increased for chlamydia and for gonorrhea. Outbreak mitigation was accelerated by cross-divisional teaming. Network measurements at time 3 showed LHD adaptation to H1N1 and budget constraints with increased centralization. Task redundancy increased dramatically after National Incident Management System training. Organizational network analysis supports LHD management with empirical evidence that can be translated into strategic decisions about communication, allocation of resources, and addressing knowledge gaps. Specific population health outcomes were traced directly to management decisions based on network evidence. The technique can help managers improve how LHDs function as organizations and contribute to our understanding of public health systems.

Coverage Predictions and Selection Criteria for Satellite Constellations.

DTIC Science & Technology

1982-12-01

of R.AI (51.50 at a Sop, of 47.9 ° , with DMi n - 00) than the pattern 10/5/2 listed here. Pattern 10/10/7 has been listed by Mozhaev I and Ballard...Mazaika 1-8,(1980) I G.V. Mozhaev The problem of continuous earth coverage and kinematically regular satellite networks. II. Kosmci . iss’ed., I, I, 59

Convergent functional genomics in addiction research - a translational approach to study candidate genes and gene networks.

PubMed

Spanagel, Rainer

2013-01-01

Convergent functional genomics (CFG) is a translational methodology that integrates in a Bayesian fashion multiple lines of evidence from studies in human and animal models to get a better understanding of the genetics of a disease or pathological behavior. Here the integration of data sets that derive from forward genetics in animals and genetic association studies including genome wide association studies (GWAS) in humans is described for addictive behavior. The aim of forward genetics in animals and association studies in humans is to identify mutations (e.g. SNPs) that produce a certain phenotype; i.e. "from phenotype to genotype". Most powerful in terms of forward genetics is combined quantitative trait loci (QTL) analysis and gene expression profiling in recombinant inbreed rodent lines or genetically selected animals for a specific phenotype, e.g. high vs. low drug consumption. By Bayesian scoring genomic information from forward genetics in animals is then combined with human GWAS data on a similar addiction-relevant phenotype. This integrative approach generates a robust candidate gene list that has to be functionally validated by means of reverse genetics in animals; i.e. "from genotype to phenotype". It is proposed that studying addiction relevant phenotypes and endophenotypes by this CFG approach will allow a better determination of the genetics of addictive behavior.

Finding gene regulatory network candidates using the gene expression knowledge base.

PubMed

Venkatesan, Aravind; Tripathi, Sushil; Sanz de Galdeano, Alejandro; Blondé, Ward; Lægreid, Astrid; Mironov, Vladimir; Kuiper, Martin

2014-12-10

Network-based approaches for the analysis of large-scale genomics data have become well established. Biological networks provide a knowledge scaffold against which the patterns and dynamics of 'omics' data can be interpreted. The background information required for the construction of such networks is often dispersed across a multitude of knowledge bases in a variety of formats. The seamless integration of this information is one of the main challenges in bioinformatics. The Semantic Web offers powerful technologies for the assembly of integrated knowledge bases that are computationally comprehensible, thereby providing a potentially powerful resource for constructing biological networks and network-based analysis. We have developed the Gene eXpression Knowledge Base (GeXKB), a semantic web technology based resource that contains integrated knowledge about gene expression regulation. To affirm the utility of GeXKB we demonstrate how this resource can be exploited for the identification of candidate regulatory network proteins. We present four use cases that were designed from a biological perspective in order to find candidate members relevant for the gastrin hormone signaling network model. We show how a combination of specific query definitions and additional selection criteria derived from gene expression data and prior knowledge concerning candidate proteins can be used to retrieve a set of proteins that constitute valid candidates for regulatory network extensions. Semantic web technologies provide the means for processing and integrating various heterogeneous information sources. The GeXKB offers biologists such an integrated knowledge resource, allowing them to address complex biological questions pertaining to gene expression. This work illustrates how GeXKB can be used in combination with gene expression results and literature information to identify new potential candidates that may be considered for extending a gene regulatory network.

Integration of QTL and bioinformatic tools to identify candidate genes for triglycerides in mice[S

PubMed Central

Leduc, Magalie S.; Hageman, Rachael S.; Verdugo, Ricardo A.; Tsaih, Shirng-Wern; Walsh, Kenneth; Churchill, Gary A.; Paigen, Beverly

2011-01-01

To identify genetic loci influencing lipid levels, we performed quantitative trait loci (QTL) analysis between inbred mouse strains MRL/MpJ and SM/J, measuring triglyceride levels at 8 weeks of age in F2 mice fed a chow diet. We identified one significant QTL on chromosome (Chr) 15 and three suggestive QTL on Chrs 2, 7, and 17. We also carried out microarray analysis on the livers of parental strains of 282 F2 mice and used these data to find cis-regulated expression QTL. We then narrowed the list of candidate genes under significant QTL using a “toolbox” of bioinformatic resources, including haplotype analysis; parental strain comparison for gene expression differences and nonsynonymous coding single nucleotide polymorphisms (SNP); cis-regulated eQTL in livers of F2 mice; correlation between gene expression and phenotype; and conditioning of expression on the phenotype. We suggest Slc25a7 as a candidate gene for the Chr 7 QTL and, based on expression differences, five genes (Polr3 h, Cyp2d22, Cyp2d26, Tspo, and Ttll12) as candidate genes for Chr 15 QTL. This study shows how bioinformatics can be used effectively to reduce candidate gene lists for QTL related to complex traits. PMID:21622629

P-glycoprotein (ABCB1) inhibited network of mitochondrion transport along microtubule and BMP signal-induced cell shape in chimpanzee left cerebrum by systems-theoretical analysis.

PubMed

Lin, Hong; Wang, Lin; Jiang, Minghu; Huang, Juxiang; Qi, Lianxiu

2012-10-01

We constructed the significant low-expression P-glycoprotein (ABCB1) inhibited transport and signal network in chimpanzee compared with high-expression (fold change ≥2) the human left cerebrum in GEO data set, by using integration of gene regulatory activated and inhibited network inference method with gene ontology (GO) analysis. Our result showed that ABCB1 transport and signal upstream network RAB2A inhibited ABCB1, and downstream ABCB1-inhibited SMAD1_2, NCK2, SLC25A46, GDF10, RASGRP1, EGFR, LRPPRC, RASSF2, RASA4, CA2, CBLB, UBR5, SLC25A16, ITGB3BP, DDIT4, PDPN, RAB2A in chimpanzee left cerebrum. We obtained that the different biological processes of ABCB1 inhibited transport and signal network repressed carbon dioxide transport, ER to Golgi vesicle-mediated transport, folic acid transport, mitochondrion transport along microtubule, water transport, BMP signaling pathway, Ras protein signal transduction, transforming growth factor beta receptor signaling pathway in chimpanzee compared with the inhibited network of the human left cerebrum, as a result of inducing inhibition of mitochondrion transport along microtubule and BMP signal-induced cell shape in chimpanzee left cerebrum. Our hypothesis was verified by the same and different biological processes of ABCB1 inhibited transport and signal network of chimpanzee compared with the corresponding activated network of chimpanzee and the human left cerebrum, respectively. Copyright © 2012 John Wiley & Sons, Ltd.

Level-2 Milestone 4797: Early Users on Max, Sequoia Visualization Cluster

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cupps, Kim C.

This report documents the fact that an early user has run successfully on Max, the Sequoia visualization cluster, ASC L2 milestone 4797: Early Users on Sequoia Visualization System (Max), due December 31, 2013. The Max visualization and data analysis cluster will provide Sequoia users with compute cycles and an interactive option for data exploration and analysis. The system will be integrated in the first quarter of FY14 and the system is expected to be moved to the classified network by the second quarter of FY14. The goal of this milestone is to have early users running their visualization and datamore » analysis work on the Max cluster on the classified network.« less

Modeling and Analysis of Hybrid Cellular/WLAN Systems with Integrated Service-Based Vertical Handoff Schemes

NASA Astrophysics Data System (ADS)

Xia, Weiwei; Shen, Lianfeng

We propose two vertical handoff schemes for cellular network and wireless local area network (WLAN) integration: integrated service-based handoff (ISH) and integrated service-based handoff with queue capabilities (ISHQ). Compared with existing handoff schemes in integrated cellular/WLAN networks, the proposed schemes consider a more comprehensive set of system characteristics such as different features of voice and data services, dynamic information about the admitted calls, user mobility and vertical handoffs in two directions. The code division multiple access (CDMA) cellular network and IEEE 802.11e WLAN are taken into account in the proposed schemes. We model the integrated networks by using multi-dimensional Markov chains and the major performance measures are derived for voice and data services. The important system parameters such as thresholds to prioritize handoff voice calls and queue sizes are optimized. Numerical results demonstrate that the proposed ISHQ scheme can maximize the utilization of overall bandwidth resources with the best quality of service (QoS) provisioning for voice and data services.

Inference and interrogation of a coregulatory network in the context of lipid accumulation in Yarrowia lipolytica.

PubMed

Trébulle, Pauline; Nicaud, Jean-Marc; Leplat, Christophe; Elati, Mohamed

2017-01-01

Complex phenotypes, such as lipid accumulation, result from cooperativity between regulators and the integration of multiscale information. However, the elucidation of such regulatory programs by experimental approaches may be challenging, particularly in context-specific conditions. In particular, we know very little about the regulators of lipid accumulation in the oleaginous yeast of industrial interest Yarrowia lipolytica . This lack of knowledge limits the development of this yeast as an industrial platform, due to the time-consuming and costly laboratory efforts required to design strains with the desired phenotypes. In this study, we aimed to identify context-specific regulators and mechanisms, to guide explorations of the regulation of lipid accumulation in Y. lipolytica . Using gene regulatory network inference, and considering the expression of 6539 genes over 26 time points from GSE35447 for biolipid production and a list of 151 transcription factors, we reconstructed a gene regulatory network comprising 111 transcription factors, 4451 target genes and 17048 regulatory interactions (YL-GRN-1) supported by evidence of protein-protein interactions. This study, based on network interrogation and wet laboratory validation (a) highlights the relevance of our proposed measure, the transcription factors influence, for identifying phases corresponding to changes in physiological state without prior knowledge (b) suggests new potential regulators and drivers of lipid accumulation and (c) experimentally validates the impact of six of the nine regulators identified on lipid accumulation, with variations in lipid content from +43.2% to -31.2% on glucose or glycerol.

Operationalizing Offensive Social Engineering for the Air Force

DTIC Science & Technology

2008-03-01

some concerns 2 of their members. The information was posted to a social networking site billing itself as military only but with no military ties. In...70 viii List of Figures Figure Page 1.1. Member Profile on a Social Networking Website [26] . . . . . . 3...Profile on a Social Networking Website [26] 1.3 Purpose Recognizing the advantages of social engineering and its current lack of incor- poration in the

A dynamical framework for integrated corridor management.

DOT National Transportation Integrated Search

2016-01-11

We develop analysis and control synthesis tools for dynamic traffic flow over networks. Our analysis : relies on exploiting monotonicity properties of the dynamics, and on adapting relevant tools from : stochastic queuing networks. We develop proport...

SpirPro: A Spirulina proteome database and web-based tools for the analysis of protein-protein interactions at the metabolic level in Spirulina (Arthrospira) platensis C1.

PubMed

Senachak, Jittisak; Cheevadhanarak, Supapon; Hongsthong, Apiradee

2015-07-29

Spirulina (Arthrospira) platensis is the only cyanobacterium that in addition to being studied at the molecular level and subjected to gene manipulation, can also be mass cultivated in outdoor ponds for commercial use as a food supplement. Thus, encountering environmental changes, including temperature stresses, is common during the mass production of Spirulina. The use of cyanobacteria as an experimental platform, especially for photosynthetic gene manipulation in plants and bacteria, is becoming increasingly important. Understanding the mechanisms and protein-protein interaction networks that underlie low- and high-temperature responses is relevant to Spirulina mass production. To accomplish this goal, high-throughput techniques such as OMICs analyses are used. Thus, large datasets must be collected, managed and subjected to information extraction. Therefore, databases including (i) proteomic analysis and protein-protein interaction (PPI) data and (ii) domain/motif visualization tools are required for potential use in temperature response models for plant chloroplasts and photosynthetic bacteria. A web-based repository was developed including an embedded database, SpirPro, and tools for network visualization. Proteome data were analyzed integrated with protein-protein interactions and/or metabolic pathways from KEGG. The repository provides various information, ranging from raw data (2D-gel images) to associated results, such as data from interaction and/or pathway analyses. This integration allows in silico analyses of protein-protein interactions affected at the metabolic level and, particularly, analyses of interactions between and within the affected metabolic pathways under temperature stresses for comparative proteomic analysis. The developed tool, which is coded in HTML with CSS/JavaScript and depicted in Scalable Vector Graphics (SVG), is designed for interactive analysis and exploration of the constructed network. SpirPro is publicly available on the web at http://spirpro.sbi.kmutt.ac.th . SpirPro is an analysis platform containing an integrated proteome and PPI database that provides the most comprehensive data on this cyanobacterium at the systematic level. As an integrated database, SpirPro can be applied in various analyses, such as temperature stress response networking analysis in cyanobacterial models and interacting domain-domain analysis between proteins of interest.

Spectral Graph Theory Analysis of Software-Defined Networks to Improve Performance and Security

DTIC Science & Technology

2015-09-01

listed with its associated IP address. 3. Hardware Components The hardware in the test bed included HP switches and Raspberry Pis . Two types of...discernible difference between the two types. The hosts in the network are Raspberry Pis [58], which are small, inexpensive computers with 10/100... Pis ran one of four operating systems: Raspbian, ArchLinux, Kali, 85 and Windows 10. All of the Raspberry Pis were configured with Iperf [59

Countering Botnets: Anomaly-Based Detection, Comprehensive Analysis, and Efficient Mitigation

DTIC Science & Technology

2011-05-01

our network prophylactic for ISPs. Using DNSRBL lists to identify address to provide specific routes into a network device that does further deep ...Notos is resilient to changes in the zone classes we selected. Services like CDNs and major web sites can add new IPs or adjust domain formats, and...less good domain names, such as file-sharing, porn -related websites, etc., most of which are not run in a professional way and have disputable

Matching Navy Recruiting Needs with Social Network Profiles Using Lexical Link Analysis. N1 FY10 Research Project

DTIC Science & Technology

2010-01-01

recruiting needs and candidate profiles – Link the features in context of dynamic social network environments, learn from on-going market...universities, companies, etc.) • Friends list fandom (fan of) , • Endorsements (supporter of) • Navy Enlisted Rating descriptions – Hard Cards...the samples into a validation and a learning set Set aside . the validation set. Use the learning set to match the recruit ratings with the

Detection of changes in gene regulatory patterns, elicited by perturbations of the Hsp90 molecular chaperone complex, by visualizing multiple experiments with an animation

PubMed Central

2011-01-01

Background To make sense out of gene expression profiles, such analyses must be pushed beyond the mere listing of affected genes. For example, if a group of genes persistently display similar changes in expression levels under particular experimental conditions, and the proteins encoded by these genes interact and function in the same cellular compartments, this could be taken as very strong indicators for co-regulated protein complexes. One of the key requirements is having appropriate tools to detect such regulatory patterns. Results We have analyzed the global adaptations in gene expression patterns in the budding yeast when the Hsp90 molecular chaperone complex is perturbed either pharmacologically or genetically. We integrated these results with publicly accessible expression, protein-protein interaction and intracellular localization data. But most importantly, all experimental conditions were simultaneously and dynamically visualized with an animation. This critically facilitated the detection of patterns of gene expression changes that suggested underlying regulatory networks that a standard analysis by pairwise comparison and clustering could not have revealed. Conclusions The results of the animation-assisted detection of changes in gene regulatory patterns make predictions about the potential roles of Hsp90 and its co-chaperone p23 in regulating whole sets of genes. The simultaneous dynamic visualization of microarray experiments, represented in networks built by integrating one's own experimental with publicly accessible data, represents a powerful discovery tool that allows the generation of new interpretations and hypotheses. PMID:21672238

Development of QSAR models using artificial neural network analysis for risk assessment of repeated-dose, reproductive, and developmental toxicities of cosmetic ingredients.

PubMed

Hisaki, Tomoka; Aiba Née Kaneko, Maki; Yamaguchi, Masahiko; Sasa, Hitoshi; Kouzuki, Hirokazu

2015-04-01

Use of laboratory animals for systemic toxicity testing is subject to strong ethical and regulatory constraints, but few alternatives are yet available. One possible approach to predict systemic toxicity of chemicals in the absence of experimental data is quantitative structure-activity relationship (QSAR) analysis. Here, we present QSAR models for prediction of maximum "no observed effect level" (NOEL) for repeated-dose, developmental and reproductive toxicities. NOEL values of 421 chemicals for repeated-dose toxicity, 315 for reproductive toxicity, and 156 for developmental toxicity were collected from Japan Existing Chemical Data Base (JECDB). Descriptors to predict toxicity were selected based on molecular orbital (MO) calculations, and QSAR models employing multiple independent descriptors as the input layer of an artificial neural network (ANN) were constructed to predict NOEL values. Robustness of the models was indicated by the root-mean-square (RMS) errors after 10-fold cross-validation (0.529 for repeated-dose, 0.508 for reproductive, and 0.558 for developmental toxicity). Evaluation of the models in terms of the percentages of predicted NOELs falling within factors of 2, 5 and 10 of the in-vivo-determined NOELs suggested that the model is applicable to both general chemicals and the subset of chemicals listed in International Nomenclature of Cosmetic Ingredients (INCI). Our results indicate that ANN models using in silico parameters have useful predictive performance, and should contribute to integrated risk assessment of systemic toxicity using a weight-of-evidence approach. Availability of predicted NOELs will allow calculation of the margin of safety, as recommended by the Scientific Committee on Consumer Safety (SCCS).

Exhaustive analysis of the modular structure of the spliceosomal assembly network: a petri net approach.

PubMed

Bortfeldt, Ralf H; Schuster, Stefan; Koch, Ina

2011-01-01

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier. Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.

Exhaustive analysis of the modular structure of the spliceosomal assembly network: a Petri net approach.

PubMed

Bortfeldt, Ralf H; Schuster, Stefan; Koch, Ina

2010-01-01

Spliceosomes are macro-complexes involving hundreds of proteins with many functional interactions. Spliceosome assembly belongs to the key processes that enable splicing of mRNA and modulate alternative splicing. A detailed list of factors involved in spliceosomal reactions has been assorted over the past decade, but, their functional interplay is often unknown and most of the present biological models cover only parts of the complete assembly process. It is a challenging task to build a computational model that integrates dispersed knowledge and combines a multitude of reaction schemes proposed earlier.Because for most reactions involved in spliceosome assembly kinetic parameters are not available, we propose a discrete modeling using Petri nets, through which we are enabled to get insights into the system's behavior via computation of structural and dynamic properties. In this paper, we compile and examine reactions from experimental reports that contribute to a functional spliceosome. All these reactions form a network, which describes the inventory and conditions necessary to perform the splicing process. The analysis is mainly based on system invariants. Transition invariants (T-invariants) can be interpreted as signaling routes through the network. Due to the huge number of T-invariants that arise with increasing network size and complexity, maximal common transition sets (MCTS) and T-clusters were used for further analysis. Additionally, we introduce a false color map representation, which allows a quick survey of network modules and the visual detection of single reactions or reaction sequences, which participate in more than one signaling route. We designed a structured model of spliceosome assembly, which combines the demands on a platform that i) can display involved factors and concurrent processes, ii) offers the possibility to run computational methods for knowledge extraction, and iii) is successively extendable as new insights into spliceosome function are reported by experimental reports. The network consists of 161 transitions (reactions) and 140 places (reactants). All reactions are part of at least one of the 71 T-invariants. These T-invariants define pathways, which are in good agreement with the current knowledge and known hypotheses on reaction sequences during spliceosome assembly, hence contributing to a functional spliceosome. We demonstrate that present knowledge, in particular of the initial part of the assembly process, describes parallelism and interaction of signaling routes, which indicate functional redundancy and reflect the dependency of spliceosome assembly initiation on different cellular conditions. The complexity of the network is further increased by two switches, which introduce alternative routes during A-complex formation in early spliceosome assembly and upon transition from the B-complex to the C-complex. By compiling known reactions into a complete network, the combinatorial nature of invariant computation leads to pathways that have previously not been described as connected routes, although their constituents were known. T-clusters divide the network into modules, which we interpret as building blocks in spliceosome maturation. We conclude that Petri net representations of large biological networks and system invariants, are well-suited as a means for validating the integration of experimental knowledge into a consistent model. Based on this network model, the design of further experiments is facilitated.

NASA Integrated Network Monitor and Control Software Architecture

NASA Technical Reports Server (NTRS)

Shames, Peter; Anderson, Michael; Kowal, Steve; Levesque, Michael; Sindiy, Oleg; Donahue, Kenneth; Barnes, Patrick

2012-01-01

The National Aeronautics and Space Administration (NASA) Space Communications and Navigation office (SCaN) has commissioned a series of trade studies to define a new architecture intended to integrate the three existing networks that it operates, the Deep Space Network (DSN), Space Network (SN), and Near Earth Network (NEN), into one integrated network that offers users a set of common, standardized, services and interfaces. The integrated monitor and control architecture utilizes common software and common operator interfaces that can be deployed at all three network elements. This software uses state-of-the-art concepts such as a pool of re-programmable equipment that acts like a configurable software radio, distributed hierarchical control, and centralized management of the whole SCaN integrated network. For this trade space study a model-based approach using SysML was adopted to describe and analyze several possible options for the integrated network monitor and control architecture. This model was used to refine the design and to drive the costing of the four different software options. This trade study modeled the three existing self standing network elements at point of departure, and then described how to integrate them using variations of new and existing monitor and control system components for the different proposed deployments under consideration. This paper will describe the trade space explored, the selected system architecture, the modeling and trade study methods, and some observations on useful approaches to implementing such model based trade space representation and analysis.

An Experimental Exploration of the Impact of Network-Level Packet Loss on Network Intrusion Detection

DTIC Science & Technology

2015-08-01

Experimental environment 5 Table 1 Hardware specifications Name Manufacture Model CPU Memory Hard Drive IP Address Bilbo Dell PowerEdge R610 Intel...10 we replayed the same hour of network traffic from the CDX 20093 that we used in our theoretical2 exploration to show the impact of our packet... replay the traffic at arbitrary speeds. Table 3 lists the speed multiplier that we used and the packet loss we observed. Table 3 Network packet loss

A nonparametric significance test for sampled networks.

PubMed

Elliott, Andrew; Leicht, Elizabeth; Whitmore, Alan; Reinert, Gesine; Reed-Tsochas, Felix

2018-01-01

Our work is motivated by an interest in constructing a protein-protein interaction network that captures key features associated with Parkinson's disease. While there is an abundance of subnetwork construction methods available, it is often far from obvious which subnetwork is the most suitable starting point for further investigation. We provide a method to assess whether a subnetwork constructed from a seed list (a list of nodes known to be important in the area of interest) differs significantly from a randomly generated subnetwork. The proposed method uses a Monte Carlo approach. As different seed lists can give rise to the same subnetwork, we control for redundancy by constructing a minimal seed list as the starting point for the significance test. The null model is based on random seed lists of the same length as a minimum seed list that generates the subnetwork; in this random seed list the nodes have (approximately) the same degree distribution as the nodes in the minimum seed list. We use this null model to select subnetworks which deviate significantly from random on an appropriate set of statistics and might capture useful information for a real world protein-protein interaction network. The software used in this paper are available for download at https://sites.google.com/site/elliottande/. The software is written in Python and uses the NetworkX library. ande.elliott@gmail.com or felix.reed-tsochas@sbs.ox.ac.uk. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

A nonparametric significance test for sampled networks

PubMed Central

Leicht, Elizabeth; Whitmore, Alan; Reinert, Gesine; Reed-Tsochas, Felix

2018-01-01

Abstract Motivation Our work is motivated by an interest in constructing a protein–protein interaction network that captures key features associated with Parkinson’s disease. While there is an abundance of subnetwork construction methods available, it is often far from obvious which subnetwork is the most suitable starting point for further investigation. Results We provide a method to assess whether a subnetwork constructed from a seed list (a list of nodes known to be important in the area of interest) differs significantly from a randomly generated subnetwork. The proposed method uses a Monte Carlo approach. As different seed lists can give rise to the same subnetwork, we control for redundancy by constructing a minimal seed list as the starting point for the significance test. The null model is based on random seed lists of the same length as a minimum seed list that generates the subnetwork; in this random seed list the nodes have (approximately) the same degree distribution as the nodes in the minimum seed list. We use this null model to select subnetworks which deviate significantly from random on an appropriate set of statistics and might capture useful information for a real world protein–protein interaction network. Availability and implementation The software used in this paper are available for download at https://sites.google.com/site/elliottande/. The software is written in Python and uses the NetworkX library. Contact ande.elliott@gmail.com or felix.reed-tsochas@sbs.ox.ac.uk Supplementary information Supplementary data are available at Bioinformatics online. PMID:29036452

Genome-wide network-based pathway analysis of CSF t-tau/Aβ1-42 ratio in the ADNI cohort.

PubMed

Cong, Wang; Meng, Xianglian; Li, Jin; Zhang, Qiushi; Chen, Feng; Liu, Wenjie; Wang, Ying; Cheng, Sipu; Yao, Xiaohui; Yan, Jingwen; Kim, Sungeun; Saykin, Andrew J; Liang, Hong; Shen, Li

2017-05-30

The cerebrospinal fluid (CSF) levels of total tau (t-tau) and Aβ 1-42 are potential early diagnostic markers for probable Alzheimer's disease (AD). The influence of genetic variation on these CSF biomarkers has been investigated in candidate or genome-wide association studies (GWAS). However, the investigation of statistically modest associations in GWAS in the context of biological networks is still an under-explored topic in AD studies. The main objective of this study is to gain further biological insights via the integration of statistical gene associations in AD with physical protein interaction networks. The CSF and genotyping data of 843 study subjects (199 CN, 85 SMC, 239 EMCI, 207 LMCI, 113 AD) from the Alzheimer's Disease Neuroimaging Initiative (ADNI) were analyzed. PLINK was used to perform GWAS on the t-tau/Aβ 1-42 ratio using quality controlled genotype data, including 563,980 single nucleotide polymorphisms (SNPs), with age, sex and diagnosis as covariates. Gene-level p-values were obtained by VEGAS2. Genes with p-value ≤ 0.05 were mapped on to a protein-protein interaction (PPI) network (9,617 nodes, 39,240 edges, from the HPRD Database). We integrated a consensus model strategy into the iPINBPA network analysis framework, and named it as CM-iPINBPA. Four consensus modules (CMs) were discovered by CM-iPINBPA, and were functionally annotated using the pathway analysis tool Enrichr. The intersection of four CMs forms a common subnetwork of 29 genes, including those related to tau phosphorylation (GSK3B, SUMO1, AKAP5, CALM1 and DLG4), amyloid beta production (CASP8, PIK3R1, PPA1, PARP1, CSNK2A1, NGFR, and RHOA), and AD (BCL3, CFLAR, SMAD1, and HIF1A). This study coupled a consensus module (CM) strategy with the iPINBPA network analysis framework, and applied it to the GWAS of CSF t-tau/Aβ1-42 ratio in an AD study. The genome-wide network analysis yielded 4 enriched CMs that share not only genes related to tau phosphorylation or amyloid beta production but also multiple genes enriching several KEGG pathways such as Alzheimer's disease, colorectal cancer, gliomas, renal cell carcinoma, Huntington's disease, and others. This study demonstrated that integration of gene-level associations with CMs could yield statistically significant findings to offer valuable biological insights (e.g., functional interaction among the protein products of these genes) and suggest high confidence candidates for subsequent analyses.

MitProNet: A Knowledgebase and Analysis Platform of Proteome, Interactome and Diseases for Mammalian Mitochondria

PubMed Central

Mao, Song; Chai, Xiaoqiang; Hu, Yuling; Hou, Xugang; Tang, Yiheng; Bi, Cheng; Li, Xiao

2014-01-01

Mitochondrion plays a central role in diverse biological processes in most eukaryotes, and its dysfunctions are critically involved in a large number of diseases and the aging process. A systematic identification of mitochondrial proteomes and characterization of functional linkages among mitochondrial proteins are fundamental in understanding the mechanisms underlying biological functions and human diseases associated with mitochondria. Here we present a database MitProNet which provides a comprehensive knowledgebase for mitochondrial proteome, interactome and human diseases. First an inventory of mammalian mitochondrial proteins was compiled by widely collecting proteomic datasets, and the proteins were classified by machine learning to achieve a high-confidence list of mitochondrial proteins. The current version of MitProNet covers 1124 high-confidence proteins, and the remainders were further classified as middle- or low-confidence. An organelle-specific network of functional linkages among mitochondrial proteins was then generated by integrating genomic features encoded by a wide range of datasets including genomic context, gene expression profiles, protein-protein interactions, functional similarity and metabolic pathways. The functional-linkage network should be a valuable resource for the study of biological functions of mitochondrial proteins and human mitochondrial diseases. Furthermore, we utilized the network to predict candidate genes for mitochondrial diseases using prioritization algorithms. All proteins, functional linkages and disease candidate genes in MitProNet were annotated according to the information collected from their original sources including GO, GEO, OMIM, KEGG, MIPS, HPRD and so on. MitProNet features a user-friendly graphic visualization interface to present functional analysis of linkage networks. As an up-to-date database and analysis platform, MitProNet should be particularly helpful in comprehensive studies of complicated biological mechanisms underlying mitochondrial functions and human mitochondrial diseases. MitProNet is freely accessible at http://bio.scu.edu.cn:8085/MitProNet. PMID:25347823

Revealing the Effects of the Herbal Pair of Euphorbia kansui and Glycyrrhiza on Hepatocellular Carcinoma Ascites with Integrating Network Target Analysis and Experimental Validation

PubMed Central

Zhang, Yanqiong; Lin, Ya; Zhao, Haiyu; Guo, Qiuyan; Yan, Chen; Lin, Na

2016-01-01

Although the herbal pair of Euphorbia kansui (GS) and Glycyrrhiza (GC) is one of the so-called "eighteen antagonistic medicaments" in Chinese medicinal literature, it is prescribed in a classic Traditional Chinese Medicine (TCM) formula Gansui-Banxia-Tang for cancerous ascites, suggesting that GS and GC may exhibit synergistic or antagonistic effects in different combination designs. Here, we modeled the effects of GS/GC combination with a target interaction network and clarified the associations between the network topologies involving the drug targets and the drug combination effects. Moreover, the "edge-betweenness" values, which is defined as the frequency with which edges are placed on the shortest paths between all pairs of modules in network, were calculated, and the ADRB1-PIK3CG interaction exhibited the greatest edge-betweenness value, suggesting its crucial role in connecting the other edges in the network. Because ADRB1 and PIK3CG were putative targets of GS and GC, respectively, and both had functional interactions with AVPR2 approved as known therapeutic target for ascites, we proposed that the ADRB1-PIK3CG-AVPR2 signal axis might be involved in the effects of the GS-GC combination on ascites. This proposal was further experimentally validated in a H22 hepatocellular carcinoma (HCC) ascites model. Collectively, this systems-level investigation integrated drug target prediction and network analysis to reveal the combination principles of the herbal pair of GS and GC. Experimental validation in an in vivo system provided convincing evidence that different combination designs of GS and GC might result in synergistic or antagonistic effects on HCC ascites that might be partially related to their regulation of the ADRB1-PIK3CG-AVPR2 signal axis. PMID:27143956

[Reembursing health-care service provider networks].

PubMed

Binder, A; Braun, G E

2015-03-01

Health-care service provider networks are regarded as an important instrument to overcome the widely criticised fragmentation and sectoral partition of the German health-care system. The first part of this paper incorporates health-care service provider networks in the field of health-care research. The system theoretical model and basic functions of health-care research are used for this purpose. Furthermore already established areas of health-care research with strong relations to health-care service provider networks are listed. The second part of this paper introduces some innovative options for reimbursing health-care service provider networks which can be regarded as some results of network-oriented health-care research. The origins are virtual budgets currently used in part to reimburse integrated care according to §§ 140a ff. SGB V. Describing and evaluating this model leads to real budgets (capitation) - a reimbursement scheme repeatedly demanded by SVR-Gesundheit (German governmental health-care advisory board), for example, however barely implemented. As a final step a direct reimbursement of networks by the German sickness fund is discussed. Advantages and challenges are shown. The development of the different reimbursement schemes is partially based on models from the USA. © Georg Thieme Verlag KG Stuttgart · New York.

A preliminary study of differentially expressed genes in expanded skin and normal skin: implications for adult skin regeneration.

PubMed

Yang, Mei; Liang, Yimin; Sheng, Lingling; Shen, Guoxiong; Liu, Kai; Gu, Bin; Meng, Fanjun; Li, Qingfeng

2011-03-01

In adults, severely damaged skin heals by scar formation and cannot regenerate to the original skin structure. However, tissue expansion is an exception, as normal skin regenerates under the mechanical stretch resulting from tissue expansion. This technique has been used clinically for defect repair and organ reconstruction for decades. However, the phenomenon of adult skin regeneration during tissue expansion has caused little attention, and the mechanism of skin regeneration during tissue expansion has not been fully understood. In this study, microarray analysis was performed on expanded human skin and normal human skin. Significant difference was observed in 77 genes, which suggest a network of several integrated cascades, including cytokines, extracellular, cytoskeletal, transmembrane molecular systems, ion or ion channels, protein kinases and transcriptional systems, is involved in the skin regeneration during expansion. Among these, the significant expression of some regeneration related genes, such as HOXA5, HOXB2 and AP1, was the first report in tissue expansion. Data in this study suggest a list of candidate genes, which may help to elucidate the fundamental mechanism of skin regeneration during tissue expansion and which may have implications for postnatal skin regeneration and therapeutic interventions in wound healing.

Wireless sensor network: an aimless gadget or a necessary tool for natural hazards warning systems

NASA Astrophysics Data System (ADS)

Hloupis, George; Stavrakas, Ilias; Triantis, Dimos

2010-05-01

The purpose of the current study is to review the current technical and scientific state of wireless sensor networks (WSNs) with application on natural hazards. WSN have received great attention from the research community in the last few years, mainly due to the theoretical and practical efforts from challenges that led to mature solutions and adoption of standards, such as Bluetooth [2] and ZigBee [3]. Wireless technology solutions allows Micro-ElectroMechanical Systems sensors (MEMS) to be integrated (with all the necessary circuitry) to small wireless capable devices, the nodes. Available MEMS today include pressure, temperature, humidity, inertial and strain-gauge sensors as well as transducers for velocity, acceleration, vibration, flow position and inclination [4]. A WSN is composed by a large number of nodes which are deployed densely adjacent to the area under monitoring. Each node collects data which transmitted to a gateway. The main requirements that WSNs must fulfilled are quite different than those of ad-hoc networks. WSNs have to be self-organized (since the positions of individual nodes are not known in advance), they must present cooperative processing of tasks (where groups of nodes cooperate in order to provide the gathered data to the user), they require security mechanisms that are adaptive to monitoring conditions and all algorithms must be energy optimized. In this paper, the state of the art in hardware, software, algorithms and protocols for WSNs, focused on natural hazards, is surveyed. Architectures for WSNs are investigated along with their advantages and drawbacks. Available research prototypes as well as commercially proposed solutions that can be used for natural hazards monitoring and early warning systems are listed and classified. [1] I.F. Akyildiz, W. Su, Y. Sankarasubramaniam, E. Cayirci, Wireless sensor networks: a survey, Comput. Networks (Elsevier) 38 (4) (2002) 393-422. [2] Dursch, A.; Yen, D.C.; Shih, D.H. Bluetooth technology: an exploratory study of the analysis and implementation frameworks. Comput. Stand. Interface. 2004, 26, 263-277. [3] Baronti, P.; Pillai, P.; Chook, V.W.C.; Chessa, S.; Gotta, A.; Hu, Y.F. Wireless sensor networks: A survey on the state of the art and the 802.15.4 and ZigBee standards. Comput. Commun. 2007, 30, 1655-1695. [4] Arampatzis, T.; Lygeros, J.; Manesis, S. A survey of applications of wireless sensors and Wireless Sensor Networks. In 2005 IEEE International Symposium on Intelligent Control & 13th Mediterranean Conference on Control and Automation. Limassol, Cyprus, 2005, 1-2, 719-724.

Network analysis of Bogotá's Ciclovía Recreativa, a self-organized multisectorial community program to promote physical activity in a middle-income country.

PubMed

Meisel, Jose D; Sarmiento, Olga L; Montes, Felipe; Martinez, Edwin O; Lemoine, Pablo D; Valdivia, Juan A; Brownson, Ross C; Zarama, Roberto

2014-01-01

Conduct a social network analysis of the health and non-health related organizations that participate in Bogotá's Ciclovía Recreativa (Ciclovía). Cross-sectional study. Ciclovía is a multisectoral community-based mass program in which streets are temporarily closed to motorized transport, allowing exclusive access to individuals for leisure activities and physical activity. Twenty-five organizations that participate in the Ciclovía. Seven variables were examined by using network analytic methods: relationship, link attributes (integration, contact, and importance), and node attributes (leadership, years in the program, and the sector of the organization). The network analytic methods were based on a visual descriptive analysis and an exponential random graph model. Analysis shows that the most central organizations in the network were outside of the Health sector and include Sports and Recreation, Government, and Security sectors. The organizations work in clusters formed by organizations of different sectors. Organization importance and structural predictors were positively related to integration, while the number of years working with Ciclovía was negatively associated with integration. Ciclovía is a network whose structure emerged as a self-organized complex system. Ciclovía of Bogotá is an example of a program with public health potential formed by organizations of multiple sectors with Sports and Recreation as the most central.

The Structure and Effectiveness of Health Systems: Exploring the Impact of System Integration in Rural China.

PubMed

Wang, Xin; Birch, Stephen; Ma, Huifen; Zhu, Weiming; Meng, Qingyue

2016-08-12

Facing the challenges of aging populations, increasing chronic diseases prevalence and health system fragmentation, there have been several pilots of integrated health systems in China. But little is known about their structure, mechanism and effectiveness. The aim of this paper is to analyze health system integration and develop recommendations for achieving integration. Huangzhong and Hualong counties in Qinghai province were studied as study sites, with only Huangzhong having implemented health system integration. Questionnaires, interviews, and health insurance records were sources of data. Social network analysis was employed to analyze integration, through structure measurement and effectiveness evaluation. Health system integration in Huangzhong is higher than in Hualong, so is system effectiveness. The patient referral network in Hualong has more "leapfrog" referrals. The information sharing networks in both counties are larger than the other types of networks. The average distance in the joint training network of Huangzhong is less than in Hualong. Meanwhile, there are deficiencies common to both systems. Both county health systems have strengths and limitations regarding system integration. The use of medical consortia in Huangzhong has contributed to system effectiveness. Future research might consider alternative more context specific models of health system integration.

Network Analysis of Epidermal Growth Factor Signaling Using Integrated Genomic, Proteomic and Phosphorylation Data

PubMed Central

Waters, Katrina M.; Liu, Tao; Quesenberry, Ryan D.; Willse, Alan R.; Bandyopadhyay, Somnath; Kathmann, Loel E.; Weber, Thomas J.; Smith, Richard D.; Wiley, H. Steven; Thrall, Brian D.

2012-01-01

To understand how integration of multiple data types can help decipher cellular responses at the systems level, we analyzed the mitogenic response of human mammary epithelial cells to epidermal growth factor (EGF) using whole genome microarrays, mass spectrometry-based proteomics and large-scale western blots with over 1000 antibodies. A time course analysis revealed significant differences in the expression of 3172 genes and 596 proteins, including protein phosphorylation changes measured by western blot. Integration of these disparate data types showed that each contributed qualitatively different components to the observed cell response to EGF and that varying degrees of concordance in gene expression and protein abundance measurements could be linked to specific biological processes. Networks inferred from individual data types were relatively limited, whereas networks derived from the integrated data recapitulated the known major cellular responses to EGF and exhibited more highly connected signaling nodes than networks derived from any individual dataset. While cell cycle regulatory pathways were altered as anticipated, we found the most robust response to mitogenic concentrations of EGF was induction of matrix metalloprotease cascades, highlighting the importance of the EGFR system as a regulator of the extracellular environment. These results demonstrate the value of integrating multiple levels of biological information to more accurately reconstruct networks of cellular response. PMID:22479638

Network integration modelling of feeder and BRT(bus rapid transit) to reduce the usage of private vehicles in Palembang’s suburban area

NASA Astrophysics Data System (ADS)

Nur'afalia, D.; Afifa, F.; Rubianto, L.; Handayeni, K. D. M. E.

2018-01-01

The aim of this research is to determine the optimal feeder network route that integrates with BRT (Bus Rapid Transit). Palembang, a high growing population city with unresolved transportation demand sector. BRT as main public transportation could not fulfill people’s demand in transportation, especially in Alang-Alang Lebar sub-district. As an impact, the usage of private vehicles increases along the movement toward the city center. The concept of Network Integration that integrates feeder network with BRT is expected to be a solution to suppress the rate of private vehicles’ usage and to improve public transportation service, so that the use of BRT will be increased in the suburban area of Palembang. The method used to identifying the optimal route using Route Analysis method is route analysis using Tranetsim 0.4. The best route is obtained based on 156 movement samples. The result is 58,7% from 199 mobility’s potency of private vehicle usage’s can be reduced if there is a feeder network’s route in Alang-Alang Lebar’s sub-district. From the result, the existance of integration between feeder network and BRT is potential enough to reduce the usage of private vehicles and supports the sustainability of transportation mobility in Palembang City.

ENFIN--A European network for integrative systems biology.

PubMed

Kahlem, Pascal; Clegg, Andrew; Reisinger, Florian; Xenarios, Ioannis; Hermjakob, Henning; Orengo, Christine; Birney, Ewan

2009-11-01

Integration of biological data of various types and the development of adapted bioinformatics tools represent critical objectives to enable research at the systems level. The European Network of Excellence ENFIN is engaged in developing an adapted infrastructure to connect databases, and platforms to enable both the generation of new bioinformatics tools and the experimental validation of computational predictions. With the aim of bridging the gap existing between standard wet laboratories and bioinformatics, the ENFIN Network runs integrative research projects to bring the latest computational techniques to bear directly on questions dedicated to systems biology in the wet laboratory environment. The Network maintains internally close collaboration between experimental and computational research, enabling a permanent cycling of experimental validation and improvement of computational prediction methods. The computational work includes the development of a database infrastructure (EnCORE), bioinformatics analysis methods and a novel platform for protein function analysis FuncNet.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Law, B E

Research involves analysis and field direction of AmeriFlux operations, and the PI provides scientific leadership of the AmeriFlux network. Activities include the coordination and quality assurance of measurements across AmeriFlux network sites, synthesis of results across the network, organizing and supporting the annual Science Team Meeting, and communicating AmeriFlux results to the scientific community and other users. Objectives of measurement research include (i) coordination of flux and biometric measurement protocols (ii) timely data delivery to the Carbon Dioxide Information and Analysis Center (CDIAC); and (iii) assurance of data quality of flux and ecosystem measurements contributed by AmeriFlux sites. Objectives ofmore » integration and synthesis activities include (i) integration of site data into network-wide synthesis products; and (ii) participation in the analysis, modeling and interpretation of network data products. Communications objectives include (i) organizing an annual meeting of AmeriFlux investigators for reporting annual flux measurements and exchanging scientific information on ecosystem carbon budgets; (ii) developing focused topics for analysis and publication; and (iii) developing data reporting protocols in support of AmeriFlux network goals.« less

Network analysis of Bogotá’s Ciclovía Recreativa, a self-organized multisectoral community program to promote physical activity in a middle-income country

PubMed Central

Meisel, Jose D; Sarmiento, Olga; Montes, Felipe; Martinez, Edwin O.; Lemoine, Pablo D; Valdivia, Juan A; Brownson, RC; Zarama, Robert

2016-01-01

Purpose Conduct a social network analysis of the health and non-health related organizations that participate in the Bogotá’s Ciclovía Recreativa (Ciclovía). Design Cross sectional study. Setting Ciclovía is a multisectoral community-based mass program in which streets are temporarily closed to motorized transport, allowing exclusive access to individuals for leisure activities and PA. Subjects 25 organizations that participate in the Ciclovía. Measures Seven variables were examined using network analytic methods: relationship, link attributes (integration, contact, and importance), and node attributes (leadership, years in the program, and the sector of the organization). Analysis The network analytic methods were based on a visual descriptive analysis and an exponential random graph model. Results Analysis shows that the most central organizations in the network were outside of the health sector and includes Sports and Recreation, Government, and Security sectors. The organizations work in clusters formed by organizations of different sectors. Organization importance and structural predictors were positively related to integration, while the number of years working with Ciclovía was negatively associated with integration. Conclusion Ciclovía is a network whose structure emerged as a self-organized complex system. Ciclovía of Bogotá is an example of a program with public health potential formed by organizations of multiple sectors with Sports and Recreation as the most central. PMID:23971523

PDB2Graph: A toolbox for identifying critical amino acids map in proteins based on graph theory.

PubMed

Niknam, Niloofar; Khakzad, Hamed; Arab, Seyed Shahriar; Naderi-Manesh, Hossein

2016-05-01

The integrative and cooperative nature of protein structure involves the assessment of topological and global features of constituent parts. Network concept takes complete advantage of both of these properties in the analysis concomitantly. High compatibility to structural concepts or physicochemical properties in addition to exploiting a remarkable simplification in the system has made network an ideal tool to explore biological systems. There are numerous examples in which different protein structural and functional characteristics have been clarified by the network approach. Here, we present an interactive and user-friendly Matlab-based toolbox, PDB2Graph, devoted to protein structure network construction, visualization, and analysis. Moreover, PDB2Graph is an appropriate tool for identifying critical nodes involved in protein structural robustness and function based on centrality indices. It maps critical amino acids in protein networks and can greatly aid structural biologists in selecting proper amino acid candidates for manipulating protein structures in a more reasonable and rational manner. To introduce the capability and efficiency of PDB2Graph in detail, the structural modification of Calmodulin through allosteric binding of Ca(2+) is considered. In addition, a mutational analysis for three well-identified model proteins including Phage T4 lysozyme, Barnase and Ribonuclease HI, was performed to inspect the influence of mutating important central residues on protein activity. Copyright © 2016 Elsevier Ltd. All rights reserved.

Compendium of NASA Langley reports on hypersonic aerodynamics

NASA Technical Reports Server (NTRS)

Sabo, Frances E.; Cary, Aubrey M.; Lawson, Shirley W.

1987-01-01

Reference is made to papers published by the Langley Research Center in various areas of hypersonic aerodynamics for the period 1950 to 1986. The research work was performed either in-house by the Center staff or by other personnel supported entirely or in part by grants or contracts. Abstracts have been included with the references when available. The references are listed chronologically and are grouped under the following general headings: (1) Aerodynamic Measurements - Single Shapes; (2) Aerodynamic Measurements - Configurations; (3) Aero-Heating; (4) Configuration Studies; (5) Propulsion Integration Experiment; (6) Propulsion Integration - Study; (7) Analysis Methods; (8) Test Techniques; and (9) Airframe Active Cooling Systems.

ForceAtlas2, a continuous graph layout algorithm for handy network visualization designed for the Gephi software.

PubMed

Jacomy, Mathieu; Venturini, Tommaso; Heymann, Sebastien; Bastian, Mathieu

2014-01-01

Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics...). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users' typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices.

ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software

PubMed Central

Jacomy, Mathieu; Venturini, Tommaso; Heymann, Sebastien; Bastian, Mathieu

2014-01-01

Gephi is a network visualization software used in various disciplines (social network analysis, biology, genomics…). One of its key features is the ability to display the spatialization process, aiming at transforming the network into a map, and ForceAtlas2 is its default layout algorithm. The latter is developed by the Gephi team as an all-around solution to Gephi users’ typical networks (scale-free, 10 to 10,000 nodes). We present here for the first time its functioning and settings. ForceAtlas2 is a force-directed layout close to other algorithms used for network spatialization. We do not claim a theoretical advance but an attempt to integrate different techniques such as the Barnes Hut simulation, degree-dependent repulsive force, and local and global adaptive temperatures. It is designed for the Gephi user experience (it is a continuous algorithm), and we explain which constraints it implies. The algorithm benefits from much feedback and is developed in order to provide many possibilities through its settings. We lay out its complete functioning for the users who need a precise understanding of its behaviour, from the formulas to graphic illustration of the result. We propose a benchmark for our compromise between performance and quality. We also explain why we integrated its various features and discuss our design choices. PMID:24914678

Network Analysis Tools: from biological networks to clusters and pathways.

PubMed

Brohée, Sylvain; Faust, Karoline; Lima-Mendez, Gipsi; Vanderstocken, Gilles; van Helden, Jacques

2008-01-01

Network Analysis Tools (NeAT) is a suite of computer tools that integrate various algorithms for the analysis of biological networks: comparison between graphs, between clusters, or between graphs and clusters; network randomization; analysis of degree distribution; network-based clustering and path finding. The tools are interconnected to enable a stepwise analysis of the network through a complete analytical workflow. In this protocol, we present a typical case of utilization, where the tasks above are combined to decipher a protein-protein interaction network retrieved from the STRING database. The results returned by NeAT are typically subnetworks, networks enriched with additional information (i.e., clusters or paths) or tables displaying statistics. Typical networks comprising several thousands of nodes and arcs can be analyzed within a few minutes. The complete protocol can be read and executed in approximately 1 h.

Charge transport network dynamics in molecular aggregates

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackson, Nicholas E.; Chen, Lin X.; Ratner, Mark A.

2016-07-20

Due to the nonperiodic nature of charge transport in disordered systems, generating insight into static charge transport networks, as well as analyzing the network dynamics, can be challenging. Here, we apply time-dependent network analysis to scrutinize the charge transport networks of two representative molecular semiconductors: a rigid n-type molecule, perylenediimide, and a flexible p-type molecule, bBDT(TDPP)2. Simulations reveal the relevant timescale for local transfer integral decorrelation to be ~100 fs, which is shown to be faster than that of a crystalline morphology of the same molecule. Using a simple graph metric, global network changes are observed over timescales competitive withmore » charge carrier lifetimes. These insights demonstrate that static charge transport networks are qualitatively inadequate, whereas average networks often overestimate network connectivity. Finally, a simple methodology for tracking dynamic charge transport properties is proposed.« less

Perioperative and ICU Healthcare Analytics within a Veterans Integrated System Network: a Qualitative Gap Analysis.

PubMed

Mudumbai, Seshadri; Ayer, Ferenc; Stefanko, Jerry

2017-08-01

Health care facilities are implementing analytics platforms as a way to document quality of care. However, few gap analyses exist on platforms specifically designed for patients treated in the Operating Room, Post-Anesthesia Care Unit, and Intensive Care Unit (ICU). As part of a quality improvement effort, we undertook a gap analysis of an existing analytics platform within the Veterans Healthcare Administration. The objectives were to identify themes associated with 1) current clinical use cases and stakeholder needs; 2) information flow and pain points; and 3) recommendations for future analytics development. Methods consisted of semi-structured interviews in 2 phases with a diverse set (n = 9) of support personnel and end users from five facilities across a Veterans Integrated Service Network. Phase 1 identified underlying needs and previous experiences with the analytics platform across various roles and operational responsibilities. Phase 2 validated preliminary feedback, lessons learned, and recommendations for improvement. Emerging themes suggested that the existing system met a small pool of national reporting requirements. However, pain points were identified with accessing data in several information system silos and performing multiple manual validation steps of data content. Notable recommendations included enhancing systems integration to create "one-stop shopping" for data, and developing a capability to perform trends analysis. Our gap analysis suggests that analytics platforms designed for surgical and ICU patients should employ approaches similar to those being used for primary care patients.

Defense switched network technology and experiments program

NASA Astrophysics Data System (ADS)

Weinstein, C. J.

1983-09-01

This report documents work performed during FY 1983 on the DCA-sponsored Defense Switched Network Technology and Experiments Program. The areas of work reported are: (1) development of routing algorithms for application in the Defense Switched Network (DSN); (2) instrumentation and integration of the Experimental Integrated Switched Network (EISN) test facility; (3) development and test of data communication techniques using DoD-standard data protocols in an integrated voice/data network; and (4) EISN system coordination and experiment planning.

Router Agent Technology for Policy-Based Network Management

NASA Technical Reports Server (NTRS)

Chow, Edward T.; Sudhir, Gurusham; Chang, Hsin-Ping; James, Mark; Liu, Yih-Chiao J.; Chiang, Winston

2011-01-01

This innovation can be run as a standalone network application on any computer in a networked environment. This design can be configured to control one or more routers (one instance per router), and can also be configured to listen to a policy server over the network to receive new policies based on the policy- based network management technology. The Router Agent Technology transforms the received policies into suitable Access Control List syntax for the routers it is configured to control. It commits the newly generated access control lists to the routers and provides feedback regarding any errors that were faced. The innovation also automatically generates a time-stamped log file regarding all updates to the router it is configured to control. This technology, once installed on a local network computer and started, is autonomous because it has the capability to keep listening to new policies from the policy server, transforming those policies to router-compliant access lists, and committing those access lists to a specified interface on the specified router on the network with any error feedback regarding commitment process. The stand-alone application is named RouterAgent and is currently realized as a fully functional (version 1) implementation for the Windows operating system and for CISCO routers.

Aberrant functional connectivity of default-mode network in type 2 diabetes patients.

PubMed

Cui, Ying; Jiao, Yun; Chen, Hua-Jun; Ding, Jie; Luo, Bing; Peng, Cheng-Yu; Ju, Sheng-Hong; Teng, Gao-Jun

2015-11-01

Type 2 diabetes mellitus is associated with increased risk for dementia. Patients with impaired cognition often show default-mode network disruption. We aimed to investigate the integrity of a default-mode network in diabetic patients by using independent component analysis, and to explore the relationship between network abnormalities, neurocognitive performance and diabetic variables. Forty-two patients with type 2 diabetes and 42 well-matched healthy controls were included and underwent resting-state functional MRI in a 3 Tesla unit. Independent component analysis was adopted to extract the default-mode network, including its anterior and posterior components. Z-maps of both sub-networks were compared between the two groups and correlated with each clinical variable. Patients showed increased connectivity around the medial prefrontal cortex in the anterior sub-network, but decreased connectivity around the posterior cingulate cortex in the posterior sub-network. The decreased connectivity in the posterior part was significantly correlated with the score on Complex Figure Test-delay recall test (r = 0.359, p = 0.020), the time spent on Trail-Making Test-part B (r = -0.346, p = 0.025) and the insulin resistance level (r = -0.404, p = 0.024). Dissociation pattern in the default-mode network was found in diabetic patients, which might provide powerful new insights into the neural mechanisms that underlie the diabetes-related cognitive decline. • Type 2 diabetes mellitus is associated with impaired cognition • Default- mode network plays a central role in maintaining normal cognition • Network connectivity within the default mode was disrupted in type 2 diabetes patients • Decreased network connectivity was correlated with cognitive performance and insulin resistance level • Disrupted default-mode network might explain the impaired cognition in diabetic population.

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach

PubMed Central

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions. PMID:29033978

Integrative Analysis of Transcription Factor Combinatorial Interactions Using a Bayesian Tensor Factorization Approach.

PubMed

Ye, Yusen; Gao, Lin; Zhang, Shihua

2017-01-01

Transcription factors play a key role in transcriptional regulation of genes and determination of cellular identity through combinatorial interactions. However, current studies about combinatorial regulation is deficient due to lack of experimental data in the same cellular environment and extensive existence of data noise. Here, we adopt a Bayesian CANDECOMP/PARAFAC (CP) factorization approach (BCPF) to integrate multiple datasets in a network paradigm for determining precise TF interaction landscapes. In our first application, we apply BCPF to integrate three networks built based on diverse datasets of multiple cell lines from ENCODE respectively to predict a global and precise TF interaction network. This network gives 38 novel TF interactions with distinct biological functions. In our second application, we apply BCPF to seven types of cell type TF regulatory networks and predict seven cell lineage TF interaction networks, respectively. By further exploring the dynamics and modularity of them, we find cell lineage-specific hub TFs participate in cell type or lineage-specific regulation by interacting with non-specific TFs. Furthermore, we illustrate the biological function of hub TFs by taking those of cancer lineage and blood lineage as examples. Taken together, our integrative analysis can reveal more precise and extensive description about human TF combinatorial interactions.

Effects of Cognitive Training on Resting-State Functional Connectivity of Default Mode, Salience, and Central Executive Networks.

PubMed

Cao, Weifang; Cao, Xinyi; Hou, Changyue; Li, Ting; Cheng, Yan; Jiang, Lijuan; Luo, Cheng; Li, Chunbo; Yao, Dezhong

2016-01-01

Neuroimaging studies have documented that aging can disrupt certain higher cognitive systems such as the default mode network (DMN), the salience network and the central executive network (CEN). The effect of cognitive training on higher cognitive systems remains unclear. This study used a 1-year longitudinal design to explore the cognitive training effect on three higher cognitive networks in healthy older adults. The community-living healthy older adults were divided into two groups: the multi-domain cognitive training group (24 sessions of cognitive training over a 3-months period) and the wait-list control group. All subjects underwent cognitive measurements and resting-state functional magnetic resonance imaging scanning at baseline and at 1 year after the training ended. We examined training-related changes in functional connectivity (FC) within and between three networks. Compared with the baseline, we observed maintained or increased FC within all three networks after training. The scans after training also showed maintained anti-correlation of FC between the DMN and CEN compared to the baseline. These findings demonstrated that cognitive training maintained or improved the functional integration within networks and the coupling between the DMN and CEN in older adults. Our findings suggested that multi-domain cognitive training can mitigate the aging-related dysfunction of higher cognitive networks.

Effects of Cognitive Training on Resting-State Functional Connectivity of Default Mode, Salience, and Central Executive Networks

PubMed Central

Cao, Weifang; Cao, Xinyi; Hou, Changyue; Li, Ting; Cheng, Yan; Jiang, Lijuan; Luo, Cheng; Li, Chunbo; Yao, Dezhong

2016-01-01

Neuroimaging studies have documented that aging can disrupt certain higher cognitive systems such as the default mode network (DMN), the salience network and the central executive network (CEN). The effect of cognitive training on higher cognitive systems remains unclear. This study used a 1-year longitudinal design to explore the cognitive training effect on three higher cognitive networks in healthy older adults. The community-living healthy older adults were divided into two groups: the multi-domain cognitive training group (24 sessions of cognitive training over a 3-months period) and the wait-list control group. All subjects underwent cognitive measurements and resting-state functional magnetic resonance imaging scanning at baseline and at 1 year after the training ended. We examined training-related changes in functional connectivity (FC) within and between three networks. Compared with the baseline, we observed maintained or increased FC within all three networks after training. The scans after training also showed maintained anti-correlation of FC between the DMN and CEN compared to the baseline. These findings demonstrated that cognitive training maintained or improved the functional integration within networks and the coupling between the DMN and CEN in older adults. Our findings suggested that multi-domain cognitive training can mitigate the aging-related dysfunction of higher cognitive networks. PMID:27148042

Measuring healthcare integration: Operationalization of a framework for a systems evaluation of palliative care structures, processes, and outcomes.

PubMed

Bainbridge, Daryl; Brazil, Kevin; Ploeg, Jenny; Krueger, Paul; Taniguchi, Alan

2016-06-01

Healthcare integration is a priority in many countries, yet there remains little direction on how to systematically evaluate this construct to inform further development. The examination of community-based palliative care networks provides an ideal opportunity for the advancement of integration measures, in consideration of how fundamental provider cohesion is to effective care at end of life. This article presents a variable-oriented analysis from a theory-based case study of a palliative care network to help bridge the knowledge gap in integration measurement. Data from a mixed-methods case study were mapped to a conceptual framework for evaluating integrated palliative care and a visual array depicting the extent of key factors in the represented palliative care network was formulated. The study included data from 21 palliative care network administrators, 86 healthcare professionals, and 111 family caregivers, all from an established palliative care network in Ontario, Canada. The framework used to guide this research proved useful in assessing qualities of integration and functioning in the palliative care network. The resulting visual array of elements illustrates that while this network performed relatively well at the multiple levels considered, room for improvement exists, particularly in terms of interventions that could facilitate the sharing of information. This study, along with the other evaluative examples mentioned, represents important initial attempts at empirically and comprehensively examining network-integrated palliative care and healthcare integration in general. © The Author(s) 2016.

The Russian-Ukrainian Observatories Network for the European Astronomical Observatory Route Project

NASA Astrophysics Data System (ADS)

Andrievsky, S. M.; Bondar, N. I.; Karetnikov, V. G.; Kazantseva, L. V.; Nefedyev, Y. A.; Pinigin, G. I.; Pozhalova, Zh. A.; Rostopchina-Shakhovskay, A. N.; Stepanov, A. V.; Tolbin, S. V.

2011-09-01

In 2004,the Center of UNESCO World Heritage has announced a new initiative "Astronomy & World Heritage" directed for search and preserving of objects,referred to astronomy,its history in a global value,historical and cultural properties. There were defined a strategy of thematic programme "Initiative" and general criteria for selecting of ancient astronomical objects and observatories. In particular, properties that are situated or have significance in relation to celestial objects or astronomical events; representations of sky and/or celestial bodies and astronomical events; observatories and instruments; properties closely connected with the history of astronomy. In 2005-2006,in accordance with the program "Initiative", information about outstanding properties connected with astronomy have been collected.In Ukraine such work was organized by astronomical expert group in Nikolaev Astronomical Observatory. In 2007, Nikolaev observatory was included to the Tentative List of UNESCO under # 5116. Later, in 2008, the network of four astronomical observatories of Ukraine in Kiev,Crimea, Nikolaev and Odessa,considering their high authenticities and integrities,was included to the Tentative List of UNESCO under # 5267 "Astronomical Observatories of Ukraine". In 2008-2009, a new project "Thematic Study" was opened as a successor of "Initiative". It includes all fields of astronomical heritage from earlier prehistory to the Space astronomy (14 themes in total). We present the Ukraine-Russian Observatories network for the "European astronomical observatory Route project". From Russia two observatories are presented: Kazan Observatory and Pulkovo Observatory in the theme "Astronomy from the Renaissance to the mid-twentieth century".The description of astronomical observatories of Ukraine is given in accordance with the project "Thematic study"; the theme "Astronomy from the Renaissance to the mid-twentieth century" - astronomical observatories in Kiev,Nikolaev and Odessa; the theme "Contemporary Astronomy" - Crimean Astrophysical Observatory. Also on the basis of collaboration between Ukraine and Russia the Russian-Ukrainian network of astronomical observatories was organized. The participation in Paris conference, on September 20-22, will be a good opportunity to present and to discuss some questions of selection, protection and preparation of Russian-Ukrainian -network to the List of UNESCO within the topic of the Project "Route of European astronomical observatories ".

Exploring MEDLINE Space with Random Indexing and Pathfinder Networks

PubMed Central

Cohen, Trevor

2008-01-01

The integration of disparate research domains is a prerequisite for the success of the translational science initiative. MEDLINE abstracts contain content from a broad range of disciplines, presenting an opportunity for the development of methods able to integrate the knowledge they contain. Latent Semantic Analysis (LSA) and related methods learn human-like associations between terms from unannotated text. However, their computational and memory demands limits their ability to address a corpus of this size. Furthermore, visualization methods previously used in conjunction with LSA have limited ability to define the local structure of the associative networks LSA learns. This paper explores these issues by (1) processing the entire MEDLINE corpus using Random Indexing, a variant of LSA, and (2) exploring learned associations using Pathfinder Networks. Meaningful associations are inferred from MEDLINE, including a drug-disease association undetected by PUBMED search. PMID:18999236

Exploring MEDLINE space with random indexing and pathfinder networks.

PubMed

Cohen, Trevor

2008-11-06

The integration of disparate research domains is a prerequisite for the success of the translational science initiative. MEDLINE abstracts contain content from a broad range of disciplines, presenting an opportunity for the development of methods able to integrate the knowledge they contain. Latent Semantic Analysis (LSA) and related methods learn human-like associations between terms from unannotated text. However, their computational and memory demands limits their ability to address a corpus of this size. Furthermore, visualization methods previously used in conjunction with LSA have limited ability to define the local structure of the associative networks LSA learns. This paper explores these issues by (1) processing the entire MEDLINE corpus using Random Indexing, a variant of LSA, and (2) exploring learned associations using Pathfinder Networks. Meaningful associations are inferred from MEDLINE, including a drug-disease association undetected by PUBMED search.

A Hybrid 3D Indoor Space Model

NASA Astrophysics Data System (ADS)

Jamali, Ali; Rahman, Alias Abdul; Boguslawski, Pawel

2016-10-01

GIS integrates spatial information and spatial analysis. An important example of such integration is for emergency response which requires route planning inside and outside of a building. Route planning requires detailed information related to indoor and outdoor environment. Indoor navigation network models including Geometric Network Model (GNM), Navigable Space Model, sub-division model and regular-grid model lack indoor data sources and abstraction methods. In this paper, a hybrid indoor space model is proposed. In the proposed method, 3D modeling of indoor navigation network is based on surveying control points and it is less dependent on the 3D geometrical building model. This research proposes a method of indoor space modeling for the buildings which do not have proper 2D/3D geometrical models or they lack semantic or topological information. The proposed hybrid model consists of topological, geometrical and semantical space.

Incorporating social network effects into cost-effectiveness analysis: a methodological contribution with application to obesity prevention

PubMed Central

Konchak, Chad; Prasad, Kislaya

2012-01-01

Objectives To develop a methodology for integrating social networks into traditional cost-effectiveness analysis (CEA) studies. This will facilitate the economic evaluation of treatment policies in settings where health outcomes are subject to social influence. Design This is a simulation study based on a Markov model. The lifetime health histories of a cohort are simulated, and health outcomes compared, under alternative treatment policies. Transition probabilities depend on the health of others with whom there are shared social ties. Setting The methodology developed is shown to be applicable in any healthcare setting where social ties affect health outcomes. The example of obesity prevention is used for illustration under the assumption that weight changes are subject to social influence. Main outcome measures Incremental cost-effectiveness ratio (ICER). Results When social influence increases, treatment policies become more cost effective (have lower ICERs). The policy of only treating individuals who span multiple networks can be more cost effective than the policy of treating everyone. This occurs when the network is more fragmented. Conclusions (1) When network effects are accounted for, they result in very different values of incremental cost-effectiveness ratios (ICERs). (2) Treatment policies can be devised to take network structure into account. The integration makes it feasible to conduct a cost-benefit evaluation of such policies. PMID:23117559

Research on the exponential growth effect on network topology: Theoretical and empirical analysis

NASA Astrophysics Data System (ADS)

Li, Shouwei; You, Zongjun

Integrated circuit (IC) industry network has been built in Yangtze River Delta with the constant expansion of IC industry. The IC industry network grows exponentially with the establishment of new companies and the establishment of contacts with old firms. Based on preferential attachment and exponential growth, the paper presents the analytical results in which the vertices degree of scale-free network follows power-law distribution p(k)˜k‑γ (γ=2β+1) and parameter β satisfies 0.5≤β≤1. At the same time, we find that the preferential attachment takes place in a dynamic local world and the size of the dynamic local world is in direct proportion to the size of whole networks. The paper also gives the analytical results of no-preferential attachment and exponential growth on random networks. The computer simulated results of the model illustrate these analytical results. Through some investigations on the enterprises, this paper at first presents the distribution of IC industry, composition of industrial chain and service chain firstly. Then, the correlative network and its analysis of industrial chain and service chain are presented. The correlative analysis of the whole IC industry is also presented at the same time. Based on the theory of complex network, the analysis and comparison of industrial chain network and service chain network in Yangtze River Delta are provided in the paper.

Altered brain activation and functional connectivity in working memory related networks in patients with type 2 diabetes: An ICA-based analysis

PubMed Central

Zhang, Yang; Lu, Shan; Liu, Chunlei; Zhang, Huimei; Zhou, Xuanhe; Ni, Changlin; Qin, Wen; Zhang, Quan

2016-01-01

Type 2 diabetes mellitus (T2DM) can cause multidimensional cognitive deficits, among which working memory (WM) is usually involved at an early stage. However, the neural substrates underlying impaired WM in T2DM patients are still unclear. To clarify this issue, we utilized functional magnetic resonance imaging (fMRI) and independent component analysis to evaluate T2DM patients for alterations in brain activation and functional connectivity (FC) in WM networks and to determine their associations with cognitive and clinical variables. Twenty complication-free T2DM patients and 19 matched healthy controls (HCs) were enrolled, and fMRI data were acquired during a block-designed 1-back WM task. The WM metrics of the T2DM patients showed no differences compared with those of the HCs, except for a slightly lower accuracy rate in the T2DM patients. Compared with the HCs, the T2DM patients demonstrated increased activation within their WM fronto-parietal networks, and activation strength was significantly correlated with WM performance. The T2DM patients also showed decreased FC within and between their WM networks. Our results indicate that the functional integration of WM sub-networks was disrupted in the complication-free T2DM patients and that strengthened regional activity in fronto-parietal networks may compensate for the WM impairment caused by T2DM. PMID:27021340

Identification of key regulators of pancreatic cancer progression through multidimensional systems-level analysis.

PubMed

Rajamani, Deepa; Bhasin, Manoj K

2016-05-03

Pancreatic cancer is an aggressive cancer with dismal prognosis, urgently necessitating better biomarkers to improve therapeutic options and early diagnosis. Traditional approaches of biomarker detection that consider only one aspect of the biological continuum like gene expression alone are limited in their scope and lack robustness in identifying the key regulators of the disease. We have adopted a multidimensional approach involving the cross-talk between the omics spaces to identify key regulators of disease progression. Multidimensional domain-specific disease signatures were obtained using rank-based meta-analysis of individual omics profiles (mRNA, miRNA, DNA methylation) related to pancreatic ductal adenocarcinoma (PDAC). These domain-specific PDAC signatures were integrated to identify genes that were affected across multiple dimensions of omics space in PDAC (genes under multiple regulatory controls, GMCs). To further pin down the regulators of PDAC pathophysiology, a systems-level network was generated from knowledge-based interaction information applied to the above identified GMCs. Key regulators were identified from the GMC network based on network statistics and their functional importance was validated using gene set enrichment analysis and survival analysis. Rank-based meta-analysis identified 5391 genes, 109 miRNAs and 2081 methylation-sites significantly differentially expressed in PDAC (false discovery rate ≤ 0.05). Bimodal integration of meta-analysis signatures revealed 1150 and 715 genes regulated by miRNAs and methylation, respectively. Further analysis identified 189 altered genes that are commonly regulated by miRNA and methylation, hence considered GMCs. Systems-level analysis of the scale-free GMCs network identified eight potential key regulator hubs, namely E2F3, HMGA2, RASA1, IRS1, NUAK1, ACTN1, SKI and DLL1, associated with important pathways driving cancer progression. Survival analysis on individual key regulators revealed that higher expression of IRS1 and DLL1 and lower expression of HMGA2, ACTN1 and SKI were associated with better survival probabilities. It is evident from the results that our hierarchical systems-level multidimensional analysis approach has been successful in isolating the converging regulatory modules and associated key regulatory molecules that are potential biomarkers for pancreatic cancer progression.

HEATH National Resource Directory on Postsecondary Education and Disability, 2001.

ERIC Educational Resources Information Center

Jones, Dottie, Ed.

Approximately 200 organizational resources concerned with postsecondary education and disability are listed and described in this directory. Resources are listed under six broad categories: (1) advocacy, access, and awareness; (2) community integration (in the arts, employment, independent living, recreation, and rehabilitation); (3)…

A directed network of Greek and Roman mythology

NASA Astrophysics Data System (ADS)

Choi, Yeon-Mu; Kim, Hyun-Joo

2007-08-01

We construct a directed network using a dictionary of Greek and Roman mythology in which the nodes represent the entries listed in the dictionary and we make directional links from an entry to other entries that appear in its explanatory part. We find that this network is clearly not a random network but a directed scale-free network in which the distributions of out-degree and in-degree follow a power-law with exponents γout≈3.0 and γin≈2.5, respectively. Also we measure several quantities which describe the topological properties of the network and compare it to that of other real networks.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Harmsen, S.C.

The telemetered southern Great Basin seismic network (SGBSN) is operated for the Department of Energy`s Yucca Mountain Project (YMP). The US Geological Survey, Branch of Earthquake and Landslide Hazards, maintained this network until September 30, 1992, at which time all operational and analysis responsibilities were transferred to the University of Nevada at Reno Seismological Laboratory (UNRSL). This report contains preliminary earthquake and chemical explosion hypocenter listings and preliminary earthquake focal mechanism solutions for USGS/SGBSN data for the period January 1, 1992 through September 30, 1992, 15:00 UTC.

Optimal cost for strengthening or destroying a given network

NASA Astrophysics Data System (ADS)

Patron, Amikam; Cohen, Reuven; Li, Daqing; Havlin, Shlomo

2017-05-01

Strengthening or destroying a network is a very important issue in designing resilient networks or in planning attacks against networks, including planning strategies to immunize a network against diseases, viruses, etc. Here we develop a method for strengthening or destroying a random network with a minimum cost. We assume a correlation between the cost required to strengthen or destroy a node and the degree of the node. Accordingly, we define a cost function c (k ) , which is the cost of strengthening or destroying a node with degree k . Using the degrees k in a network and the cost function c (k ) , we develop a method for defining a list of priorities of degrees and for choosing the right group of degrees to be strengthened or destroyed that minimizes the total price of strengthening or destroying the entire network. We find that the list of priorities of degrees is universal and independent of the network's degree distribution, for all kinds of random networks. The list of priorities is the same for both strengthening a network and for destroying a network with minimum cost. However, in spite of this similarity, there is a difference between their pc, the critical fraction of nodes that has to be functional to guarantee the existence of a giant component in the network.

Optimal cost for strengthening or destroying a given network.

PubMed

Patron, Amikam; Cohen, Reuven; Li, Daqing; Havlin, Shlomo

2017-05-01

Strengthening or destroying a network is a very important issue in designing resilient networks or in planning attacks against networks, including planning strategies to immunize a network against diseases, viruses, etc. Here we develop a method for strengthening or destroying a random network with a minimum cost. We assume a correlation between the cost required to strengthen or destroy a node and the degree of the node. Accordingly, we define a cost function c(k), which is the cost of strengthening or destroying a node with degree k. Using the degrees k in a network and the cost function c(k), we develop a method for defining a list of priorities of degrees and for choosing the right group of degrees to be strengthened or destroyed that minimizes the total price of strengthening or destroying the entire network. We find that the list of priorities of degrees is universal and independent of the network's degree distribution, for all kinds of random networks. The list of priorities is the same for both strengthening a network and for destroying a network with minimum cost. However, in spite of this similarity, there is a difference between their p_{c}, the critical fraction of nodes that has to be functional to guarantee the existence of a giant component in the network.

Holding-based network of nations based on listed energy companies: An empirical study on two-mode affiliation network of two sets of actors

NASA Astrophysics Data System (ADS)

Li, Huajiao; Fang, Wei; An, Haizhong; Gao, Xiangyun; Yan, Lili

2016-05-01

Economic networks in the real world are not homogeneous; therefore, it is important to study economic networks with heterogeneous nodes and edges to simulate a real network more precisely. In this paper, we present an empirical study of the one-mode derivative holding-based network constructed by the two-mode affiliation network of two sets of actors using the data of worldwide listed energy companies and their shareholders. First, we identify the primitive relationship in the two-mode affiliation network of the two sets of actors. Then, we present the method used to construct the derivative network based on the shareholding relationship between two sets of actors and the affiliation relationship between actors and events. After constructing the derivative network, we analyze different topological features on the node level, edge level and entire network level and explain the meanings of the different values of the topological features combining the empirical data. This study is helpful for expanding the usage of complex networks to heterogeneous economic networks. For empirical research on the worldwide listed energy stock market, this study is useful for discovering the inner relationships between the nations and regions from a new perspective.

Proteomic analysis of intestinal tissues from mice fed with Lentinula edodes-derived polysaccharides.

PubMed

Xu, Xiaofei; Yang, Jiguo; Ning, Zhengxiang; Zhang, Xuewu

2016-01-01

Lentinula edodes-derived polysaccharides are well known for their immunomodulation and antitumor activities. However, the mechanisms of action have not been fully elucidated. This study presents proteomic analysis of the colon and small intestine from mice fed with an immunostimulating heteropolysaccharide L2 from the fruit body of L. edodes. Two-dimensional gel electrophoresis (2-DE) and MALDI-TOF-TOF MS/MS were employed to characterize the protein profiles. Twenty nine gel spots representing 20 proteins in colon tissues and 38 gel spots in small intestine tissues representing 23 proteins were identified as showing significant changes in abundance. These differential proteins in abundance are mainly involved in metabolism, binding, structural components, and response to stimulus. Protein-protein interaction network analysis demonstrated mapping of the 20 colon proteins to a 7-protein and a 3-protein sub-network, and mapping of the 23 small intestine proteins to a 9-protein and a 5-protein sub-network. All the 40 altered proteins were integrated into a unified network containing 25 proteins, suggesting the existence of a concerted mechanism, although acting on the colon and small intestine separately. These findings facilitate the understanding of the regulatory mechanism in response to L2 treatment.

Discovery of new candidate genes for rheumatoid arthritis through integration of genetic association data with expression pathway analysis.

PubMed

Shchetynsky, Klementy; Diaz-Gallo, Lina-Marcella; Folkersen, Lasse; Hensvold, Aase Haj; Catrina, Anca Irinel; Berg, Louise; Klareskog, Lars; Padyukov, Leonid

2017-02-02

Here we integrate verified signals from previous genetic association studies with gene expression and pathway analysis for discovery of new candidate genes and signaling networks, relevant for rheumatoid arthritis (RA). RNA-sequencing-(RNA-seq)-based expression analysis of 377 genes from previously verified RA-associated loci was performed in blood cells from 5 newly diagnosed, non-treated patients with RA, 7 patients with treated RA and 12 healthy controls. Differentially expressed genes sharing a similar expression pattern in treated and untreated RA sub-groups were selected for pathway analysis. A set of "connector" genes derived from pathway analysis was tested for differential expression in the initial discovery cohort and validated in blood cells from 73 patients with RA and in 35 healthy controls. There were 11 qualifying genes selected for pathway analysis and these were grouped into two evidence-based functional networks, containing 29 and 27 additional connector molecules. The expression of genes, corresponding to connector molecules was then tested in the initial RNA-seq data. Differences in the expression of ERBB2, TP53 and THOP1 were similar in both treated and non-treated patients with RA and an additional nine genes were differentially expressed in at least one group of patients compared to healthy controls. The ERBB2, TP53. THOP1 expression profile was successfully replicated in RNA-seq data from peripheral blood mononuclear cells from healthy controls and non-treated patients with RA, in an independent collection of samples. Integration of RNA-seq data with findings from association studies, and consequent pathway analysis implicate new candidate genes, ERBB2, TP53 and THOP1 in the pathogenesis of RA.

The Intellectual Structure of Metacognitive Scaffolding in Science Education: A Co-Citation Network Analysis

ERIC Educational Resources Information Center

Tang, Kai-Yu; Wang, Chia-Yu; Chang, Hsin-Yi; Chen, Sufen; Lo, Hao-Chang; Tsai, Chin-Chung

2016-01-01

The issues of metacognitive scaffolding in science education (MSiSE) have become increasingly popular and important. Differing from previous content reviews, this study proposes a series of quantitative computer-based analyses by integrating document co-citation analysis, social network analysis, and exploratory factor analysis to explore the…

Harmonising and semantically linking key variables from in-situ observing networks of an Integrated Atlantic Ocean Observing System, AtlantOS

NASA Astrophysics Data System (ADS)

Darroch, Louise; Buck, Justin

2017-04-01

Atlantic Ocean observation is currently undertaken through loosely-coordinated, in-situ observing networks, satellite observations and data management arrangements at regional, national and international scales. The EU Horizon 2020 AtlantOS project aims to deliver an advanced framework for the development of an Integrated Atlantic Ocean Observing System that strengthens the Global Ocean Observing System (GOOS) and contributes to the aims of the Galway Statement on Atlantic Ocean Cooperation. One goal is to ensure that data from different and diverse in-situ observing networks are readily accessible and useable to a wider community, including the international ocean science community and other stakeholders in this field. To help achieve this goal, the British Oceanographic Data Centre (BODC) produced a parameter matrix to harmonise data exchange, data flow and data integration for the key variables acquired by multiple in-situ AtlantOS observing networks such as ARGO, Seafloor Mapping and OceanSITES. Our solution used semantic linking of controlled vocabularies and metadata for parameters that were "mappable" to existing EU and international standard vocabularies. An AtlantOS Essential Variables list of terms (aggregated level) based on Global Climate Observing System (GCOS) Essential Climate Variables (ECV), GOOS Essential Ocean Variables (EOV) and other key network variables was defined and published on the Natural Environment Research Council (NERC) Vocabulary Server (version 2.0) as collection A05 (http://vocab.nerc.ac.uk/collection/A05/current/). This new vocabulary was semantically linked to standardised metadata for observed properties and units that had been validated by the AtlantOS community: SeaDataNet parameters (P01), Climate and Forecast (CF) Standard Names (P07) and SeaDataNet units (P06). Observed properties were mapped to biological entities from the internationally assured AphiaID from the WOrld Register of Marine Species (WoRMS), http://www.marinespecies.org/aphia.php?p=webservice. The AtlantOS parameter matrix offers a way to harmonise the globally important variables (such as ECVs and EOVs) from in-situ observing networks that use different flavours of exchange formats based on SeaDataNet and CF parameter metadata. It also offers a way to standardise data in the wider Integrated Ocean Observing System. It uses sustainable and trusted standardised vocabularies that are governed by internationally renowned and long-standing organisations and is interoperable through the use of persistent resource identifiers, such as URNs and PURLs. It is the first step to integrating and serving data in a variety of international exchange formats using Application programming interfaces (API) improving both data discoverability and utility for users.

A Highly Functional Decision Paradigm Based on Nonlinear Adaptive Genetic Algorithm

DTIC Science & Technology

1997-10-07

significant speedup. p£ lC <$jALTnimm SCTED & 14. SUBJECT TERMS Network Topology Optimization, Mathlink, Mathematica Plug-In, GA Route Optimizer, DSP...operations per second 2.4 Gbytes/second sustainable on-chip data transfer rate 400 Mb/s off-chip peak transfer rate Layer-to-layer interconnection...SecondHighestDist# = DistanceArray%(IndexList%(ChromeGene%(i%, 1) -1), IndexList%( Chrom eGene%(i%, 2) - 1)) For j% = 1 To StrandLength% - 1 ’If highest distance

Capitation: strategies for success with managed care contracts.

PubMed

Kuklierus, A

1997-01-01

With enrollments in HMOs increasing at double digit rates, independent practice associations, integrated medical groups, hospitals and specialty networks are experiencing a substantial increase in the share of their business paid for through capitation. Experience has shown that once one contract is signed, many are sure to follow. Providers must make sure each contract signed is financially sound for the organization. Then they must be able to manage and monitor contracts long after the ink is dry. This column provides a brief overview ad list of pointers for organizations moving into the managed care arena.

Selective impairment of hippocampus and posterior hub areas in Alzheimer's disease: an MEG-based multiplex network study.

PubMed

Yu, Meichen; Engels, Marjolein M A; Hillebrand, Arjan; van Straaten, Elisabeth C W; Gouw, Alida A; Teunissen, Charlotte; van der Flier, Wiesje M; Scheltens, Philip; Stam, Cornelis J

2017-05-01

Although frequency-specific network analyses have shown that functional brain networks are altered in patients with Alzheimer's disease, the relationships between these frequency-specific network alterations remain largely unknown. Multiplex network analysis is a novel network approach to study complex systems consisting of subsystems with different types of connectivity patterns. In this study, we used magnetoencephalography to integrate five frequency-band specific brain networks in a multiplex framework. Previous structural and functional brain network studies have consistently shown that hub brain areas are selectively disrupted in Alzheimer's disease. Accordingly, we hypothesized that hub regions in the multiplex brain networks are selectively targeted in patients with Alzheimer's disease in comparison to healthy control subjects. Eyes-closed resting-state magnetoencephalography recordings from 27 patients with Alzheimer's disease (60.6 ± 5.4 years, 12 females) and 26 controls (61.8 ± 5.5 years, 14 females) were projected onto atlas-based regions of interest using beamforming. Subsequently, source-space time series for both 78 cortical and 12 subcortical regions were reconstructed in five frequency bands (delta, theta, alpha 1, alpha 2 and beta band). Multiplex brain networks were constructed by integrating frequency-specific magnetoencephalography networks. Functional connections between all pairs of regions of interests were quantified using a phase-based coupling metric, the phase lag index. Several multiplex hub and heterogeneity metrics were computed to capture both overall importance of each brain area and heterogeneity of the connectivity patterns across frequency-specific layers. Different nodal centrality metrics showed consistently that several hub regions, particularly left hippocampus, posterior parts of the default mode network and occipital regions, were vulnerable in patients with Alzheimer's disease compared to control subjects. Of note, these detected vulnerable hubs in Alzheimer's disease were absent in each individual frequency-specific network, thus showing the value of integrating the networks. The connectivity patterns of these vulnerable hub regions in the patients were heterogeneously distributed across layers. Perturbed cognitive function and abnormal cerebrospinal fluid amyloid-β42 levels correlated positively with the vulnerability of the hub regions in patients with Alzheimer's disease. Our analysis therefore demonstrates that the magnetoencephalography-based multiplex brain networks contain important information that cannot be revealed by frequency-specific brain networks. Furthermore, this indicates that functional networks obtained in different frequency bands do not act as independent entities. Overall, our multiplex network study provides an effective framework to integrate the frequency-specific networks with different frequency patterns and reveal neuropathological mechanism of hub disruption in Alzheimer's disease. © The Author (2017). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Trends in Wait-list Mortality in Children Listed for Heart Transplantation in the United States

PubMed Central

Singh, Tajinder P.; Almond, Christopher S.; Piercey, Gary; Gauvreau, Kimberlee

2014-01-01

We sought to evaluate trends in overall and race-specific pediatric heart transplant (HT) wait-list mortality in the United States (US) during the last 20 years. We identified all children <18 years old listed for primary HT in the US during 1989–2009 (N=8096, 62% white, 19% black, 13% Hispanic, 6% other) using the Organ Procurement and Transplant Network database. Wait-list mortality was assessed in 4 successive eras (1989–1994, 1995–1999, 2000–2004, and 2005–2009). Overall wait-list mortality declined in successive eras (26%, 23%, 18% and 13%, respectively). The decline across eras remained significant in adjusted analysis (hazard ratio [HR] 0.70 in successive eras, 95% confidence interval [CI] 0.67, 0.74) and was 67% lower for children listed during 2005–2009 vs. those listed during 1989–1994 (HR 0.33, CI 0.28, 0.39). In models stratified by race, wait-list mortality decreased in all racial groups in successive eras. In models stratified by era, minority children were not at higher risk of wait-list mortality in the most recent era. We conclude that the risk of wait-list mortality among US children listed for HT has decreased by two-thirds during the last 20 years. Racial gaps in wait-list mortality present variably in the past are not present in the current era. PMID:21883920

GLOBECOM '88 - IEEE Global Telecommunications Conference and Exhibition, Hollywood, FL, Nov. 28-Dec. 1, 1988, Conference Record. Volumes 1, 2, & 3

NASA Astrophysics Data System (ADS)

Various papers on communications for the information age are presented. Among the general topics considered are: telematic services and terminals, satellite communications, telecommunications mangaement network, control of integrated broadband networks, advances in digital radio systems, the intelligent network, broadband networks and services deployment, future switch architectures, performance analysis of computer networks, advances in spread spectrum, optical high-speed LANs, and broadband switching and networks. Also addressed are: multiple access protocols, video coding techniques, modulation and coding, photonic switching, SONET terminals and applications, standards for video coding, digital switching, progress in MANs, mobile and portable radio, software design for improved maintainability, multipath propagation and advanced countermeasure, data communication, network control and management, fiber in the loop, network algorithm and protocols, and advances in computer communications.

Psychological interventions for positive symptoms in schizophrenia: protocol for a network meta-analysis of randomised controlled trials

PubMed Central

Salanti, Georgia; Reitmeir, Cornelia; Wallis, Sofia; Barbui, Corrado; Leucht, Stefan

2018-01-01

Introduction There is rising awareness that we need multidisciplinary approaches integrating psychological treatments for schizophrenia, but a comprehensive evidence based on their relative efficacy is lacking. We will conduct a network meta-analysis (NMA), integrating direct and indirect comparisons from randomised controlled trials (RCTs) to rank psychological treatments for schizophrenia according to their efficacy, acceptability and tolerability. Methods and analysis We will include all RCTs comparing a psychological treatment aimed at positive symptoms of schizophrenia with another psychological intervention or with a no treatment condition (waiting-list and treatment as usual). We will include studies on adult patients with schizophrenia, excluding specific subpopulations (eg, first-episode patients or patients with psychiatric comorbidities). Primary outcome will be the change in positive symptoms on a published rating scale. Secondary outcomes will be acceptability (dropout), change in overall and negative symptoms of schizophrenia, response, relapse, adherence, depression, quality of life, functioning and adverse events. Published and unpublished studies will be sought through database searches, trial registries and websites. Study selection and data extraction will be conducted by at least two independent reviewers. We will conduct random-effects NMA to synthesise all evidences for each outcome and obtain a comprehensive ranking of all treatments. NMA will be conducted in Stata and R within a frequentist framework. The risk of bias in studies will be evaluated using the Cochrane Risk of Bias tool and the credibility of the evidence will be evaluated using an adaptation of the Grading of Recommendations Assessment, Development and Evaluation framework to NMA, recommended by the Cochrane guidance. Subgroup and sensitivity analyses will be conducted to assess the robustness of the findings. Ethics and dissemination No ethical issues are foreseen. Results from this study will be published in peer-reviewed journals and presented at relevant conferences. PROSPERO registration number CRD42017067795. PMID:29540411

Netlang: A software for the linguistic analysis of corpora by means of complex networks

PubMed Central

Serna Salazar, Diego; Isaza, Gustavo; Castillo Ossa, Luis F.; Bedia, Manuel G.

2017-01-01

To date there is no software that directly connects the linguistic analysis of a conversation to a network program. Networks programs are able to extract statistical information from data basis with information about systems of interacting elements. Language has also been conceived and studied as a complex system. However, most proposals do not analyze language according to linguistic theory, but use instead computational systems that should save time at the price of leaving aside many crucial aspects for linguistic theory. Some approaches to network studies on language do apply precise linguistic analyses, made by a linguist. The problem until now has been the lack of interface between the analysis of a sentence and its integration into the network that could be managed by a linguist and that could save the analysis of any language. Previous works have used old software that was not created for these purposes and that often produced problems with some idiosyncrasies of the target language. The desired interface should be able to deal with the syntactic peculiarities of a particular language, the options of linguistic theory preferred by the user and the preservation of morpho-syntactic information (lexical categories and syntactic relations between items). Netlang is the first program able to do that. Recently, a new kind of linguistic analysis has been developed, which is able to extract a complexity pattern from the speaker's linguistic production which is depicted as a network where words are inside nodes, and these nodes connect each other by means of edges or links (the information inside the edge can be syntactic, semantic, etc.). The Netlang software has become the bridge between rough linguistic data and the network program. Netlang has integrated and improved the functions of programs used in the past, namely the DGA annotator and two scripts (ToXML.pl and Xml2Pairs.py) used for transforming and pruning data. Netlang allows the researcher to make accurate linguistic analysis by means of syntactic dependency relations between words, while tracking record of the nature of such syntactic relationships (subject, object, etc). The Netlang software is presented as a new tool that solve many problems detected in the past. The most important improvement is that Netlang integrates three past applications into one program, and is able to produce a series of file formats that can be read by a network program. Through the Netlang software, the linguistic network analysis based on syntactic analyses, characterized for its low cost and the completely non-invasive procedure aims to evolve into a sufficiently fine grained tool for clinical diagnosis in potential cases of language disorders. PMID:28832598

Netlang: A software for the linguistic analysis of corpora by means of complex networks.

PubMed

Barceló-Coblijn, Lluís; Serna Salazar, Diego; Isaza, Gustavo; Castillo Ossa, Luis F; Bedia, Manuel G

2017-01-01

To date there is no software that directly connects the linguistic analysis of a conversation to a network program. Networks programs are able to extract statistical information from data basis with information about systems of interacting elements. Language has also been conceived and studied as a complex system. However, most proposals do not analyze language according to linguistic theory, but use instead computational systems that should save time at the price of leaving aside many crucial aspects for linguistic theory. Some approaches to network studies on language do apply precise linguistic analyses, made by a linguist. The problem until now has been the lack of interface between the analysis of a sentence and its integration into the network that could be managed by a linguist and that could save the analysis of any language. Previous works have used old software that was not created for these purposes and that often produced problems with some idiosyncrasies of the target language. The desired interface should be able to deal with the syntactic peculiarities of a particular language, the options of linguistic theory preferred by the user and the preservation of morpho-syntactic information (lexical categories and syntactic relations between items). Netlang is the first program able to do that. Recently, a new kind of linguistic analysis has been developed, which is able to extract a complexity pattern from the speaker's linguistic production which is depicted as a network where words are inside nodes, and these nodes connect each other by means of edges or links (the information inside the edge can be syntactic, semantic, etc.). The Netlang software has become the bridge between rough linguistic data and the network program. Netlang has integrated and improved the functions of programs used in the past, namely the DGA annotator and two scripts (ToXML.pl and Xml2Pairs.py) used for transforming and pruning data. Netlang allows the researcher to make accurate linguistic analysis by means of syntactic dependency relations between words, while tracking record of the nature of such syntactic relationships (subject, object, etc). The Netlang software is presented as a new tool that solve many problems detected in the past. The most important improvement is that Netlang integrates three past applications into one program, and is able to produce a series of file formats that can be read by a network program. Through the Netlang software, the linguistic network analysis based on syntactic analyses, characterized for its low cost and the completely non-invasive procedure aims to evolve into a sufficiently fine grained tool for clinical diagnosis in potential cases of language disorders.

Early grey matter changes in structural covariance networks in Huntington's disease.

PubMed

Coppen, Emma M; van der Grond, Jeroen; Hafkemeijer, Anne; Rombouts, Serge A R B; Roos, Raymund A C

2016-01-01

Progressive subcortical changes are known to occur in Huntington's disease (HD), a hereditary neurodegenerative disorder. Less is known about the occurrence and cohesion of whole brain grey matter changes in HD. We aimed to detect network integrity changes in grey matter structural covariance networks and examined relationships with clinical assessments. Structural magnetic resonance imaging data of premanifest HD ( n  = 30), HD patients (n = 30) and controls (n = 30) was used to identify ten structural covariance networks based on a novel technique using the co-variation of grey matter with independent component analysis in FSL. Group differences were studied controlling for age and gender. To explore whether our approach is effective in examining grey matter changes, regional voxel-based analysis was additionally performed. Premanifest HD and HD patients showed decreased network integrity in two networks compared to controls. One network included the caudate nucleus, precuneous and anterior cingulate cortex (in HD p  < 0.001, in pre-HD p  = 0.003). One other network contained the hippocampus, premotor, sensorimotor, and insular cortices (in HD p  < 0.001, in pre-HD p  = 0.023). Additionally, in HD patients only, decreased network integrity was observed in a network including the lingual gyrus, intracalcarine, cuneal, and lateral occipital cortices ( p  = 0.032). Changes in network integrity were significantly associated with scores of motor and neuropsychological assessments. In premanifest HD, voxel-based analyses showed pronounced volume loss in the basal ganglia, but less prominent in cortical regions. Our results suggest that structural covariance might be a sensitive approach to reveal early grey matter changes, especially for premanifest HD.

Integrated Advanced Microwave Sounding Unit-A (AMSU-A). As-Designed Parts List: Electrical, Electronic and Electromechanical (EEE) As-Designed Parts List

NASA Technical Reports Server (NTRS)

Lorenz, E.

1999-01-01

This report comprises the Electrical, Electronic, and Electromechanical (EEE) As Designed Parts List to be used in the Integrated Advanced Microwave Sounding Unit-A (AMSU-A) instrument. The purpose of the EEE As-Designed Parts List is to provide a listing of EEE parts identified for use on the Integrated AMSU-A. All EEE parts used on the AMSU-A must meet the parts control requirements as defined in the Parts Control Plan (POP). All part applications are reviewed by the Parts Control Board (PCB) and granted approval if POP requirements are met. The "As Designed Parts Lists" indicates PCB approval status, and thus also serves as the Program Approved Parts List.

Metabolic Networks Integrative Cardiac Health Project (ICHP) - Center of Excellence

DTIC Science & Technology

2016-08-01

Award Number: TITLE: Metabolic Networks Integrative Cardiac Health Project (ICHP) - Center of Excellence PRINCIPAL INVESTIGATOR: COL (Ret) Marina N...2016 2. REPORT TYPE FINAL 3. DATES COVERED (From - To) 29 Sep 2011 – 31 May 2016 4. TITLE AND SUBTITLE "Metabolic Networks Integrative Cardiac Health...ABSTRACT The Integrative Cardiac Health Project (ICHP) aims to lead the way in Cardiovascular Disease (CVD) Prevention by conducting novel research

Coca-Cola - a model of transparency in research partnerships? A network analysis of Coca-Cola's research funding (2008-2016).

PubMed

Serôdio, Paulo M; McKee, Martin; Stuckler, David

2018-06-01

To (i) evaluate the extent to which Coca-Cola's 'Transparency Lists' of 218 researchers that it funds are comprehensive; (ii) map all scientific research acknowledging funding from Coca-Cola; (iii) identify those institutions, authors and research topics funded by Coca-Cola; and (iv) use Coca-Cola's disclosure to gauge whether its funded researchers acknowledge the source of funding. Using Web of Science Core Collection database, we retrieved all studies declaring receipt of direct funding from the Coca-Cola brand, published between 2008 and 2016. Using conservative eligibility criteria, we iteratively removed studies and recreated Coca-Cola's transparency lists using our data. We used network analysis and structural topic modelling to assess the structure, organization and thematic focus of Coca-Cola's research enterprise, and string matching to evaluate the completeness of Coca-Cola's transparency lists. Three hundred and eighty-nine articles, published in 169 different journals, and authored by 907 researchers, cite funding from The Coca-Cola Company. Of these, Coca-Cola acknowledges funding forty-two authors (<5 %). We observed that the funded research focuses mostly on nutrition and emphasizes the importance of physical activity and the concept of 'energy balance'. The Coca-Cola Company appears to have failed to declare a comprehensive list of its research activities. Further, several funded authors appear to have failed to declare receipt of funding. Most of Coca-Cola's research support is directed towards physical activity and disregards the role of diet in obesity. Despite initiatives for greater transparency of research funding, the full scale of Coca-Cola's involvement is still not known.

Integrated Advanced Microwave Sounding Unit-A (AMSU-A). As-Designed Parts List: Electrical, Electronic, and Electromechanical (EEE) As-Built Parts List for the AMSU-A Instruments

NASA Technical Reports Server (NTRS)

2000-01-01

This is the As-Designed Parts List, Electrical, Electronic, and Electromechanical (EEE) As-Built Parts Lists For The AMSU-A Instruments, for the Integrated Advanced Microwave Sounding Unit-A (AMSU-A).

Functional connectivity changes in second language vocabulary learning.

PubMed

Ghazi Saidi, Ladan; Perlbarg, Vincent; Marrelec, Guillaume; Pélégrini-Issac, Mélani; Benali, Habib; Ansaldo, Ana-Inés

2013-01-01

Functional connectivity changes in the language network (Price, 2010), and in a control network involved in second language (L2) processing (Abutalebi & Green, 2007) were examined in a group of Persian (L1) speakers learning French (L2) words. Measures of network integration that characterize the global integrative state of a network (Marrelec, Bellec et al., 2008) were gathered, in the shallow and consolidation phases of L2 vocabulary learning. Functional connectivity remained unchanged across learning phases for L1, whereas total, between- and within-network integration levels decreased as proficiency for L2 increased. The results of this study provide the first functional connectivity evidence regarding the dynamic role of the language processing and cognitive control networks in L2 learning (Abutalebi, Cappa, & Perani, 2005; Altarriba & Heredia, 2008; Leonard et al., 2011; Parker-Jones et al., 2011). Thus, increased proficiency results in a higher degree of automaticity and lower cognitive effort (Segalowitz & Hulstijn, 2005). Copyright © 2012 Elsevier Inc. All rights reserved.

76 FR 50188 - Notice of Proposed Methodology for the Delaware River and Bay Integrated List Water Quality...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-08-12

... Integrated List Water Quality Assessment AGENCY: Delaware River Basin Commission. ACTION: Notice. SUMMARY... Integrated List Water Quality Assessment is available for review and comment. DATES: Comments must be... should have the phrase ``Water Quality Assessment 2012'' in the subject line and should include the name...

Changes in the interaction of resting-state neural networks from adolescence to adulthood.

PubMed

Stevens, Michael C; Pearlson, Godfrey D; Calhoun, Vince D

2009-08-01

This study examined how the mutual interactions of functionally integrated neural networks during resting-state fMRI differed between adolescence and adulthood. Independent component analysis (ICA) was used to identify functionally connected neural networks in 100 healthy participants aged 12-30 years. Hemodynamic timecourses that represented integrated neural network activity were analyzed with tools that quantified system "causal density" estimates, which indexed the proportion of significant Granger causality relationships among system nodes. Mutual influences among networks decreased with age, likely reflecting stronger within-network connectivity and more efficient between-network influences with greater development. Supplemental tests showed that this normative age-related reduction in causal density was accompanied by fewer significant connections to and from each network, regional increases in the strength of functional integration within networks, and age-related reductions in the strength of numerous specific system interactions. The latter included paths between lateral prefrontal-parietal circuits and "default mode" networks. These results contribute to an emerging understanding that activity in widely distributed networks thought to underlie complex cognition influences activity in other networks. (c) 2009 Wiley-Liss, Inc.

EnviroAtlas - NatureServe Analysis of Imperiled or Federally Listed Species by HUC-12 for the Conterminous United States

EPA Pesticide Factsheets

This EnviroAtlas dataset includes analysis by NatureServe of species that are Imperiled (G1/G2) or Listed under the U.S. Endangered Species Act (ESA) by 12-digit Hydrologic Units (HUCs). The analysis results are for use and publication by both the LandScope America website and by the EnviroAtlas. Results are provided for the total number of Aquatic Associated G1-G2/ESA species, the total number of Wetland Associated G1-G2/ESA species, the total number of Terrestrial Associated G1-G2/ESA species, and the total number of Unknown Habitat Association G1-G2/ESA species in each HUC12. NatureServe is a non-profit organization dedicated to developing and providing information about the world's plants, animals, and ecological communities. NatureServe works in partnership with 82 independent Natural Heritage programs and Conservation Data Centers that gather scientific information on rare species and ecosystems in the United States, Latin America, and Canada (the Natural Heritage Network). NatureServe is a leading source for biodiversity information that is essential for effective conservation action. This dataset was produced by NatureServe to support research and online mapping activities related to EnviroAtlas. EnviroAtlas (https://www.epa.gov/enviroatlas) allows the user to interact with a web-based, easy-to-use, mapping application to view and analyze multiple ecosystem services for the contiguous United States. The dataset is available as downloadable data

Integrative Genomics Reveals Novel Molecular Pathways and Gene Networks for Coronary Artery Disease

PubMed Central

Mäkinen, Ville-Petteri; Civelek, Mete; Meng, Qingying; Zhang, Bin; Zhu, Jun; Levian, Candace; Huan, Tianxiao; Segrè, Ayellet V.; Ghosh, Sujoy; Vivar, Juan; Nikpay, Majid; Stewart, Alexandre F. R.; Nelson, Christopher P.; Willenborg, Christina; Erdmann, Jeanette; Blakenberg, Stefan; O'Donnell, Christopher J.; März, Winfried; Laaksonen, Reijo; Epstein, Stephen E.; Kathiresan, Sekar; Shah, Svati H.; Hazen, Stanley L.; Reilly, Muredach P.; Lusis, Aldons J.; Samani, Nilesh J.; Schunkert, Heribert; Quertermous, Thomas; McPherson, Ruth; Yang, Xia; Assimes, Themistocles L.

2014-01-01

The majority of the heritability of coronary artery disease (CAD) remains unexplained, despite recent successes of genome-wide association studies (GWAS) in identifying novel susceptibility loci. Integrating functional genomic data from a variety of sources with a large-scale meta-analysis of CAD GWAS may facilitate the identification of novel biological processes and genes involved in CAD, as well as clarify the causal relationships of established processes. Towards this end, we integrated 14 GWAS from the CARDIoGRAM Consortium and two additional GWAS from the Ottawa Heart Institute (25,491 cases and 66,819 controls) with 1) genetics of gene expression studies of CAD-relevant tissues in humans, 2) metabolic and signaling pathways from public databases, and 3) data-driven, tissue-specific gene networks from a multitude of human and mouse experiments. We not only detected CAD-associated gene networks of lipid metabolism, coagulation, immunity, and additional networks with no clear functional annotation, but also revealed key driver genes for each CAD network based on the topology of the gene regulatory networks. In particular, we found a gene network involved in antigen processing to be strongly associated with CAD. The key driver genes of this network included glyoxalase I (GLO1) and peptidylprolyl isomerase I (PPIL1), which we verified as regulatory by siRNA experiments in human aortic endothelial cells. Our results suggest genetic influences on a diverse set of both known and novel biological processes that contribute to CAD risk. The key driver genes for these networks highlight potential novel targets for further mechanistic studies and therapeutic interventions. PMID:25033284

MAP3S precipitation chemistry network. Third periodic summary report, July 1978-December 1979

DOE Office of Scientific and Technical Information (OSTI.GOV)

Not Available

1980-05-01

The MAP3S Precipitation Chemistry Network consists of eight collection sites in the northeastern United States. Precipitation event samples are collected by cooperating site operators, using specially developed sampling equipment. In this, the third periodic summary report, are listed field and concentration data for the period July 1, 1978 to December 31, 1979. Over three years' samples have been collected at most of the sites, which went into operation between September 1976 and October 1978. Samples are chemically analyzed at a central laboratory for 13 pollutant species. Weekly samples in addition to event samples were collected over a 1 1/2 yearmore » period at three sites. Analysis of one year's results indicates that there is little difference between the concentrations collected by the two methods in terms of seasonal precipitation-weighted means for all species except dissolved SO/sub 2/. Event samples tend to average about 25% higher in SO/sub 2/ than weekly samples.« less

Advanced Satellite Research Project: SCAR Research Database. Bibliographic analysis

NASA Technical Reports Server (NTRS)

Pelton, Joseph N.

1991-01-01

The literature search was provided to locate and analyze the most recent literature that was relevant to the research. This was done by cross-relating books, articles, monographs, and journals that relate to the following topics: (1) Experimental Systems - Advanced Communications Technology Satellite (ACTS), and (2) Integrated System Digital Network (ISDN) and Advance Communication Techniques (ISDN and satellites, ISDN standards, broadband ISDN, flame relay and switching, computer networks and satellites, satellite orbits and technology, satellite transmission quality, and network configuration). Bibliographic essay on literature citations and articles reviewed during the literature search task is provided.

The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research.

PubMed

Cano, Isaac; Tényi, Ákos; Schueller, Christine; Wolff, Martin; Huertas Migueláñez, M Mercedes; Gomez-Cabrero, David; Antczak, Philipp; Roca, Josep; Cascante, Marta; Falciani, Francesco; Maier, Dieter

2014-11-28

Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data. The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice. The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http://www.copdknowledgebase.eu.

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments

PubMed Central

Avalappampatty Sivasamy, Aneetha; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T2 method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T2 statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better. PMID:26357668

A Dynamic Intrusion Detection System Based on Multivariate Hotelling's T2 Statistics Approach for Network Environments.

PubMed

Sivasamy, Aneetha Avalappampatty; Sundan, Bose

2015-01-01

The ever expanding communication requirements in today's world demand extensive and efficient network systems with equally efficient and reliable security features integrated for safe, confident, and secured communication and data transfer. Providing effective security protocols for any network environment, therefore, assumes paramount importance. Attempts are made continuously for designing more efficient and dynamic network intrusion detection models. In this work, an approach based on Hotelling's T(2) method, a multivariate statistical analysis technique, has been employed for intrusion detection, especially in network environments. Components such as preprocessing, multivariate statistical analysis, and attack detection have been incorporated in developing the multivariate Hotelling's T(2) statistical model and necessary profiles have been generated based on the T-square distance metrics. With a threshold range obtained using the central limit theorem, observed traffic profiles have been classified either as normal or attack types. Performance of the model, as evaluated through validation and testing using KDD Cup'99 dataset, has shown very high detection rates for all classes with low false alarm rates. Accuracy of the model presented in this work, in comparison with the existing models, has been found to be much better.

Reverse engineering biological networks :applications in immune responses to bio-toxins.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Martino, Anthony A.; Sinclair, Michael B.; Davidson, George S.

Our aim is to determine the network of events, or the regulatory network, that defines an immune response to a bio-toxin. As a model system, we are studying T cell regulatory network triggered through tyrosine kinase receptor activation using a combination of pathway stimulation and time-series microarray experiments. Our approach is composed of five steps (1) microarray experiments and data error analysis, (2) data clustering, (3) data smoothing and discretization, (4) network reverse engineering, and (5) network dynamics analysis and fingerprint identification. The technological outcome of this study is a suite of experimental protocols and computational tools that reverse engineermore » regulatory networks provided gene expression data. The practical biological outcome of this work is an immune response fingerprint in terms of gene expression levels. Inferring regulatory networks from microarray data is a new field of investigation that is no more than five years old. To the best of our knowledge, this work is the first attempt that integrates experiments, error analyses, data clustering, inference, and network analysis to solve a practical problem. Our systematic approach of counting, enumeration, and sampling networks matching experimental data is new to the field of network reverse engineering. The resulting mathematical analyses and computational tools lead to new results on their own and should be useful to others who analyze and infer networks.« less

Brain network segregation and integration during an epoch-related working memory fMRI experiment.

PubMed

Fransson, Peter; Schiffler, Björn C; Thompson, William Hedley

2018-05-17

The characterization of brain subnetwork segregation and integration has previously focused on changes that are detectable at the level of entire sessions or epochs of imaging data. In this study, we applied time-varying functional connectivity analysis together with temporal network theory to calculate point-by-point estimates in subnetwork segregation and integration during an epoch-based (2-back, 0-back, baseline) working memory fMRI experiment as well as during resting-state. This approach allowed us to follow task-related changes in subnetwork segregation and integration at a high temporal resolution. At a global level, the cognitively more taxing 2-back epochs elicited an overall stronger response of integration between subnetworks compared to the 0-back epochs. Moreover, the visual, sensorimotor and fronto-parietal subnetworks displayed characteristic and distinct temporal profiles of segregation and integration during the 0- and 2-back epochs. During the interspersed epochs of baseline, several subnetworks, including the visual, fronto-parietal, cingulo-opercular and dorsal attention subnetworks showed pronounced increases in segregation. Using a drift diffusion model we show that the response time for the 2-back trials are correlated with integration for the fronto-parietal subnetwork and correlated with segregation for the visual subnetwork. Our results elucidate the fast-evolving events with regard to subnetwork integration and segregation that occur in an epoch-related task fMRI experiment. Our findings suggest that minute changes in subnetwork integration are of importance for task performance. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Extracting neuronal functional network dynamics via adaptive Granger causality analysis.

PubMed

Sheikhattar, Alireza; Miran, Sina; Liu, Ji; Fritz, Jonathan B; Shamma, Shihab A; Kanold, Patrick O; Babadi, Behtash

2018-04-24

Quantifying the functional relations between the nodes in a network based on local observations is a key challenge in studying complex systems. Most existing time series analysis techniques for this purpose provide static estimates of the network properties, pertain to stationary Gaussian data, or do not take into account the ubiquitous sparsity in the underlying functional networks. When applied to spike recordings from neuronal ensembles undergoing rapid task-dependent dynamics, they thus hinder a precise statistical characterization of the dynamic neuronal functional networks underlying adaptive behavior. We develop a dynamic estimation and inference paradigm for extracting functional neuronal network dynamics in the sense of Granger, by integrating techniques from adaptive filtering, compressed sensing, point process theory, and high-dimensional statistics. We demonstrate the utility of our proposed paradigm through theoretical analysis, algorithm development, and application to synthetic and real data. Application of our techniques to two-photon Ca 2+ imaging experiments from the mouse auditory cortex reveals unique features of the functional neuronal network structures underlying spontaneous activity at unprecedented spatiotemporal resolution. Our analysis of simultaneous recordings from the ferret auditory and prefrontal cortical areas suggests evidence for the role of rapid top-down and bottom-up functional dynamics across these areas involved in robust attentive behavior.

A new approach to build VPLS with auto-discovery mechanism

NASA Astrophysics Data System (ADS)

Dong, Ximing; Yu, Shaohua

2005-11-01

VPLS is the key technology implemented to provide Layer 2 bridge-like services, connecting dispersed locations to work in a switched LAN over an MPLS backbone. However, implementing VPLS requires creating a complex matrix of services and locations that quickly becomes difficult to configure and maintain. To address this complexity, this paper proposes a new approach to automate the configuration and maintenance of VPLS networks, a node-discovery process in which each router advertises its VPLS-enabled status and capabilities to all other routers. Our approach can be summarized into four steps. (1) Discover other VPLS PE nodes with VPLS capabilities and create the VPLS capable PE routers list. We introduce a finite state machine which includes four states to illustrate the process how a VPLS peer can be discovered and the peer relations be kept alive. (2) Build MPLS LSP tunnels to all the PE routers in the list, according to the advertised VPLS protocol capabilities. (3) Use the lists to create targeted-LDP sessions for VPLS services discovery. (4) VC label assignment. The PE edge routers exchanges messages to define VC labels and bind them with each built PWE. The suggested auto-discovery mechanism is sensitive to any service provider's topology change and customer's service modification. The dynamic process for the FIB building, MAC address learning and withdrawal, is also covered as the result of VPLS auto-discovery. The suggested mechanism can be implemented as a software module and could be seamlessly integrated with currently deployed Metro Ethernet routing and switching platform.

Where we stand, where we are moving: Surveying computational techniques for identifying miRNA genes and uncovering their regulatory role.

PubMed

Kleftogiannis, Dimitrios; Korfiati, Aigli; Theofilatos, Konstantinos; Likothanassis, Spiros; Tsakalidis, Athanasios; Mavroudi, Seferina

2013-06-01

Traditional biology was forced to restate some of its principles when the microRNA (miRNA) genes and their regulatory role were firstly discovered. Typically, miRNAs are small non-coding RNA molecules which have the ability to bind to the 3'untraslated region (UTR) of their mRNA target genes for cleavage or translational repression. Existing experimental techniques for their identification and the prediction of the target genes share some important limitations such as low coverage, time consuming experiments and high cost reagents. Hence, many computational methods have been proposed for these tasks to overcome these limitations. Recently, many researchers emphasized on the development of computational approaches to predict the participation of miRNA genes in regulatory networks and to analyze their transcription mechanisms. All these approaches have certain advantages and disadvantages which are going to be described in the present survey. Our work is differentiated from existing review papers by updating the methodologies list and emphasizing on the computational issues that arise from the miRNA data analysis. Furthermore, in the present survey, the various miRNA data analysis steps are treated as an integrated procedure whose aims and scope is to uncover the regulatory role and mechanisms of the miRNA genes. This integrated view of the miRNA data analysis steps may be extremely useful for all researchers even if they work on just a single step. Copyright © 2013 Elsevier Inc. All rights reserved.

The Human Thalamus Is an Integrative Hub for Functional Brain Networks

PubMed Central

Bertolero, Maxwell A.

2017-01-01

The thalamus is globally connected with distributed cortical regions, yet the functional significance of this extensive thalamocortical connectivity remains largely unknown. By performing graph-theoretic analyses on thalamocortical functional connectivity data collected from human participants, we found that most thalamic subdivisions display network properties that are capable of integrating multimodal information across diverse cortical functional networks. From a meta-analysis of a large dataset of functional brain-imaging experiments, we further found that the thalamus is involved in multiple cognitive functions. Finally, we found that focal thalamic lesions in humans have widespread distal effects, disrupting the modular organization of cortical functional networks. This converging evidence suggests that the human thalamus is a critical hub region that could integrate diverse information being processed throughout the cerebral cortex as well as maintain the modular structure of cortical functional networks. SIGNIFICANCE STATEMENT The thalamus is traditionally viewed as a passive relay station of information from sensory organs or subcortical structures to the cortex. However, the thalamus has extensive connections with the entire cerebral cortex, which can also serve to integrate information processing between cortical regions. In this study, we demonstrate that multiple thalamic subdivisions display network properties that are capable of integrating information across multiple functional brain networks. Moreover, the thalamus is engaged by tasks requiring multiple cognitive functions. These findings support the idea that the thalamus is involved in integrating information across cortical networks. PMID:28450543

Software for Allocating Resources in the Deep Space Network

NASA Technical Reports Server (NTRS)

Wang, Yeou-Fang; Borden, Chester; Zendejas, Silvino; Baldwin, John

2003-01-01

TIGRAS 2.0 is a computer program designed to satisfy a need for improved means for analyzing the tracking demands of interplanetary space-flight missions upon the set of ground antenna resources of the Deep Space Network (DSN) and for allocating those resources. Written in Microsoft Visual C++, TIGRAS 2.0 provides a single rich graphical analysis environment for use by diverse DSN personnel, by connecting to various data sources (relational databases or files) based on the stages of the analyses being performed. Notable among the algorithms implemented by TIGRAS 2.0 are a DSN antenna-load-forecasting algorithm and a conflict-aware DSN schedule-generating algorithm. Computers running TIGRAS 2.0 can also be connected using SOAP/XML to a Web services server that provides analysis services via the World Wide Web. TIGRAS 2.0 supports multiple windows and multiple panes in each window for users to view and use information, all in the same environment, to eliminate repeated switching among various application programs and Web pages. TIGRAS 2.0 enables the use of multiple windows for various requirements, trajectory-based time intervals during which spacecraft are viewable, ground resources, forecasts, and schedules. Each window includes a time navigation pane, a selection pane, a graphical display pane, a list pane, and a statistics pane.

Systems genomics analysis centered on epigenetic inheritance supports development of a unified theory of biology.

PubMed

Sharma, Abhay

2015-11-01

New discoveries are increasingly demanding integration of epigenetics, molecular biology, genomic networks and physiology with evolution. This article provides a proof of concept for evolutionary transgenerational systems biology, proposed recently in the context of epigenetic inheritance in mammals. Gene set enrichment analysis of available genome-level mammalian data presented here seem consistent with the concept that: (1) heritable information about environmental effects in somatic cells is communicated to the germline by circulating microRNAs (miRNAs) or other RNAs released in physiological fluids; (2) epigenetic factors including miRNA-like small RNAs, DNA methylation and histone modifications are propagated across generations via gene networks; and (3) inherited epigenetic variations in the form of methylated cytosines are fixed in the population as thymines over the evolutionary time course. The analysis supports integration of physiology and epigenetics with inheritance and evolution. This may catalyze efforts to develop a unified theory of biology. © 2015. Published by The Company of Biologists Ltd.

The top-cited articles in medical education: a bibliometric analysis.

PubMed

Azer, Samy A

2015-08-01

To identify and examine the characteristics of the 50 top-cited articles in medical education. Two searches were conducted in the Web of Knowledge database in March 2014: a search of medical education journals in the category "Education, Scientific Discipline" (List A) and a keyword search across all journals (List B). Articles identified were reviewed for citation count, country of origin, article type, journal, authors, and publication year. Both lists included 56 articles, not 50, because articles with the same absolute number of citations shared the same rank. The majority of List A articles were published in Academic Medicine (34; 60.7%) and Medical Education (16; 28.6%). In List B, 27 articles (48.2%) were published in medical education journals, 19 (33.9%) in general medicine and surgery journals, and 10 (17.9%) in higher education and educational psychology journals. Twenty-six articles were included in both lists, with different rankings. Reviews and articles constituted the majority of articles; there were only 8 research papers in List A and 13 in List B. Articles mainly originated from the United States, Canada, the Netherlands, and the United Kingdom. The majority were published from 1979 to 2007. There was no correlation between year and citation count. The finding that over half of List B articles were published in nonmedical education journals is consistent with medical education's integrated nature and subspecialty breadth. Twenty of these articles were among their respective non-medical-education journals' 50 top-cited papers, showing that medical education articles can compete with subject-based articles.

Modelling the structure of a ceRNA-theoretical, bipartite microRNA-mRNA interaction network regulating intestinal epithelial cellular pathways using R programming.

PubMed

Robinson, J M; Henderson, W A

2018-01-12

We report a method using functional-molecular databases and network modelling to identify hypothetical mRNA-miRNA interaction networks regulating intestinal epithelial barrier function. The model forms a data-analysis component of our cell culture experiments, which produce RNA expression data from Nanostring Technologies nCounter ® system. The epithelial tight-junction (TJ) and actin cytoskeleton interact as molecular components of the intestinal epithelial barrier. Upstream regulation of TJ-cytoskeleton interaction is effected by the Rac/Rock/Rho signaling pathway and other associated pathways which may be activated or suppressed by extracellular signaling from growth factors, hormones, and immune receptors. Pathway activations affect epithelial homeostasis, contributing to degradation of the epithelial barrier associated with osmotic dysregulation, inflammation, and tumor development. The complexity underlying miRNA-mRNA interaction networks represents a roadblock for prediction and validation of competing-endogenous RNA network function. We developed a network model to identify hypothetical co-regulatory motifs in a miRNA-mRNA interaction network related to epithelial function. A mRNA-miRNA interaction list was generated using KEGG and miRWalk2.0 databases. R-code was developed to quantify and visualize inherent network structures. We identified a sub-network with a high number of shared, targeting miRNAs, of genes associated with cellular proliferation and cancer, including c-MYC and Cyclin D.

Inferring the interplay between network structure and market effects in Bitcoin

NASA Astrophysics Data System (ADS)

Kondor, Dániel; Csabai, István; Szüle, János; Pósfai, Márton; Vattay, Gábor

2014-12-01

A main focus in economics research is understanding the time series of prices of goods and assets. While statistical models using only the properties of the time series itself have been successful in many aspects, we expect to gain a better understanding of the phenomena involved if we can model the underlying system of interacting agents. In this article, we consider the history of Bitcoin, a novel digital currency system, for which the complete list of transactions is available for analysis. Using this dataset, we reconstruct the transaction network between users and analyze changes in the structure of the subgraph induced by the most active users. Our approach is based on the unsupervised identification of important features of the time variation of the network. Applying the widely used method of Principal Component Analysis to the matrix constructed from snapshots of the network at different times, we are able to show how structural changes in the network accompany significant changes in the exchange price of bitcoins.

Integration and Analysis of Neighbor Discovery and Link Quality Estimation in Wireless Sensor Networks

PubMed Central

Radi, Marjan; Dezfouli, Behnam; Abu Bakar, Kamalrulnizam; Abd Razak, Shukor

2014-01-01

Network connectivity and link quality information are the fundamental requirements of wireless sensor network protocols to perform their desired functionality. Most of the existing discovery protocols have only focused on the neighbor discovery problem, while a few number of them provide an integrated neighbor search and link estimation. As these protocols require a careful parameter adjustment before network deployment, they cannot provide scalable and accurate network initialization in large-scale dense wireless sensor networks with random topology. Furthermore, performance of these protocols has not entirely been evaluated yet. In this paper, we perform a comprehensive simulation study on the efficiency of employing adaptive protocols compared to the existing nonadaptive protocols for initializing sensor networks with random topology. In this regard, we propose adaptive network initialization protocols which integrate the initial neighbor discovery with link quality estimation process to initialize large-scale dense wireless sensor networks without requiring any parameter adjustment before network deployment. To the best of our knowledge, this work is the first attempt to provide a detailed simulation study on the performance of integrated neighbor discovery and link quality estimation protocols for initializing sensor networks. This study can help system designers to determine the most appropriate approach for different applications. PMID:24678277

HTS-Net: An integrated regulome-interactome approach for establishing network regulation models in high-throughput screenings

PubMed Central

Rioualen, Claire; Da Costa, Quentin; Chetrit, Bernard; Charafe-Jauffret, Emmanuelle; Ginestier, Christophe

2017-01-01

High-throughput RNAi screenings (HTS) allow quantifying the impact of the deletion of each gene in any particular function, from virus-host interactions to cell differentiation. However, there has been less development for functional analysis tools dedicated to RNAi analyses. HTS-Net, a network-based analysis program, was developed to identify gene regulatory modules impacted in high-throughput screenings, by integrating transcription factors-target genes interaction data (regulome) and protein-protein interaction networks (interactome) on top of screening z-scores. HTS-Net produces exhaustive HTML reports for results navigation and exploration. HTS-Net is a new pipeline for RNA interference screening analyses that proves better performance than simple gene rankings by z-scores, by re-prioritizing genes and replacing them in their biological context, as shown by the three studies that we reanalyzed. Formatted input data for the three studied datasets, source code and web site for testing the system are available from the companion web site at http://htsnet.marseille.inserm.fr/. We also compared our program with existing algorithms (CARD and hotnet2). PMID:28949986

Bacterial molecular networks: bridging the gap between functional genomics and dynamical modelling.

PubMed

van Helden, Jacques; Toussaint, Ariane; Thieffry, Denis

2012-01-01

This introductory review synthesizes the contents of the volume Bacterial Molecular Networks of the series Methods in Molecular Biology. This volume gathers 9 reviews and 16 method chapters describing computational protocols for the analysis of metabolic pathways, protein interaction networks, and regulatory networks. Each protocol is documented by concrete case studies dedicated to model bacteria or interacting populations. Altogether, the chapters provide a representative overview of state-of-the-art methods for data integration and retrieval, network visualization, graph analysis, and dynamical modelling.

Network-Assisted Investigation of Combined Causal Signals from Genome-Wide Association Studies in Schizophrenia

PubMed Central

Jia, Peilin; Wang, Lily; Fanous, Ayman H.; Pato, Carlos N.; Edwards, Todd L.; Zhao, Zhongming

2012-01-01

With the recent success of genome-wide association studies (GWAS), a wealth of association data has been accomplished for more than 200 complex diseases/traits, proposing a strong demand for data integration and interpretation. A combinatory analysis of multiple GWAS datasets, or an integrative analysis of GWAS data and other high-throughput data, has been particularly promising. In this study, we proposed an integrative analysis framework of multiple GWAS datasets by overlaying association signals onto the protein-protein interaction network, and demonstrated it using schizophrenia datasets. Building on a dense module search algorithm, we first searched for significantly enriched subnetworks for schizophrenia in each single GWAS dataset and then implemented a discovery-evaluation strategy to identify module genes with consistent association signals. We validated the module genes in an independent dataset, and also examined them through meta-analysis of the related SNPs using multiple GWAS datasets. As a result, we identified 205 module genes with a joint effect significantly associated with schizophrenia; these module genes included a number of well-studied candidate genes such as DISC1, GNA12, GNA13, GNAI1, GPR17, and GRIN2B. Further functional analysis suggested these genes are involved in neuronal related processes. Additionally, meta-analysis found that 18 SNPs in 9 module genes had P meta<1×10−4, including the gene HLA-DQA1 located in the MHC region on chromosome 6, which was reported in previous studies using the largest cohort of schizophrenia patients to date. These results demonstrated our bi-directional network-based strategy is efficient for identifying disease-associated genes with modest signals in GWAS datasets. This approach can be applied to any other complex diseases/traits where multiple GWAS datasets are available. PMID:22792057

Revealing the Strong Functional Association of adipor2 and cdh13 with adipoq: A Gene Network Study.

PubMed

Bag, Susmita; Anbarasu, Anand

2015-04-01

In the present study, we have analyzed functional gene interactions of adiponectin gene (adipoq). The key role of adipoq is in regulating energy homeostasis and it functions as a novel signaling molecule for adipose tissue. Modules of highly inter-connected genes in disease-specific adipoq network are derived by integrating gene function and protein interaction data. Among twenty genes in adipoq web, adipoq is effectively conjoined with two genes: Adiponectin receptor 2 (adipor2) and cadherin 13 (cdh13). The functional analysis is done via ontological briefing and candidate disease identification. We observed that the highly efficient-interlinked genes connected with adipoq are adipor2 and cdh13. Interestingly, the ontological aspect of adipor2 and cdh13 in the adipoq network reveal the fact that adipoq and adipor2 are involved mostly in glucose and lipid metabolic processes. The gene cdh13 indulge in cell adhesion process with adipoq and adipor2. Our computational gene web analysis also predicts potential candidate disease recognition, thus indicating the involvement of adipoq, adipor2, and cdh13 with not only with obesity but also with breast cancer, leukemia, renal cancer, lung cancer, and cervical cancer. The current study provides researchers a comprehensible layout of adipoq network, its functional strategies and candidate disease approach associated with adipoq network.

Network reconstruction and systems analysis of plant cell wall deconstruction by Neurospora crassa.

PubMed

Samal, Areejit; Craig, James P; Coradetti, Samuel T; Benz, J Philipp; Eddy, James A; Price, Nathan D; Glass, N Louise

2017-01-01

Plant biomass degradation by fungal-derived enzymes is rapidly expanding in economic importance as a clean and efficient source for biofuels. The ability to rationally engineer filamentous fungi would facilitate biotechnological applications for degradation of plant cell wall polysaccharides. However, incomplete knowledge of biomolecular networks responsible for plant cell wall deconstruction impedes experimental efforts in this direction. To expand this knowledge base, a detailed network of reactions important for deconstruction of plant cell wall polysaccharides into simple sugars was constructed for the filamentous fungus Neurospora crassa . To reconstruct this network, information was integrated from five heterogeneous data types: functional genomics, transcriptomics, proteomics, genetics, and biochemical characterizations. The combined information was encapsulated into a feature matrix and the evidence weighted to assign annotation confidence scores for each gene within the network. Comparative analyses of RNA-seq and ChIP-seq data shed light on the regulation of the plant cell wall degradation network, leading to a novel hypothesis for degradation of the hemicellulose mannan. The transcription factor CLR-2 was subsequently experimentally shown to play a key role in the mannan degradation pathway of N. crassa . Here we built a network that serves as a scaffold for integration of diverse experimental datasets. This approach led to the elucidation of regulatory design principles for plant cell wall deconstruction by filamentous fungi and a novel function for the transcription factor CLR-2. This expanding network will aid in efforts to rationally engineer industrially relevant hyper-production strains.

Proteomic Analysis of Virus-Host Interactions in an Infectious Context Using Recombinant Viruses*

PubMed Central

Komarova, Anastassia V.; Combredet, Chantal; Meyniel-Schicklin, Laurène; Chapelle, Manuel; Caignard, Grégory; Camadro, Jean-Michel; Lotteau, Vincent; Vidalain, Pierre-Olivier; Tangy, Frédéric

2011-01-01

RNA viruses exhibit small-sized genomes encoding few proteins, but still establish complex networks of interactions with host cell components to achieve replication and spreading. Ideally, these virus-host protein interactions should be mapped directly in infected cell culture, but such a high standard is often difficult to reach when using conventional approaches. We thus developed a new strategy based on recombinant viruses expressing tagged viral proteins to capture both direct and indirect physical binding partners during infection. As a proof of concept, we engineered a recombinant measles virus (MV) expressing one of its virulence factors, the MV-V protein, with a One-STrEP amino-terminal tag. This allowed virus-host protein complex analysis directly from infected cells by combining modified tandem affinity chromatography and mass spectrometry analysis. Using this approach, we established a prosperous list of 245 cellular proteins interacting either directly or indirectly with MV-V, and including four of the nine already known partners of this viral factor. These interactions were highly specific of MV-V because they were not recovered when the nucleoprotein MV-N, instead of MV-V, was tagged. Besides key components of the antiviral response, cellular proteins from mitochondria, ribosomes, endoplasmic reticulum, protein phosphatase 2A, and histone deacetylase complex were identified for the first time as prominent targets of MV-V and the critical role of the later protein family in MV replication was addressed. Most interestingly, MV-V showed some preferential attachment to essential proteins in the human interactome network, as assessed by centrality and interconnectivity measures. Furthermore, the list of MV-V interactors also showed a massive enrichment for well-known targets of other viruses. Altogether, this clearly supports our approach based on reverse genetics of viruses combined with high-throughput proteomics to probe the interaction network that viruses establish in infected cells. PMID:21911578

Comparative Performance of Broadcast Bus Local Area Networks with Voice and Data Traffic

DTIC Science & Technology

1987-03-01

networks [Maxemchuk & Netravali 85, Weinstein & Forgie 831. Others have dealt with economic aspects of voice/data networks [ Gitman & Frank 78] and...88. North Holland, Amsterdam, 1981. [ Gitman & Frank 78] I. Gitman & H. Frank. Economic Analysis of Integrated Voice and Data Networks: A Case Study

A Network Flow Analysis of the Nitrogen Metabolism in Beijing, China.

PubMed

Zhang, Yan; Lu, Hanjing; Fath, Brian D; Zheng, Hongmei; Sun, Xiaoxi; Li, Yanxian

2016-08-16

Rapid urbanization results in high nitrogen flows and subsequent environmental consequences. In this study, we identified the main metabolic components (nitrogen inputs, flows, and outputs) and used ecological network analysis to track the direct and integral (direct + indirect) metabolic flows of nitrogen in Beijing, China, from 1996 to 2012 and to quantify the structure of Beijing's nitrogen metabolic processes. We found that Beijing's input of new reactive nitrogen (Q, which represents nitrogen obtained from the atmosphere or nitrogen-containing materials used in production and consumption to support human activities) increased from 431 Gg in 1996 to 507 Gg in 2012. Flows to the industry, atmosphere, and household, and components of the system were clearly largest, with total integrated inputs plus outputs from these nodes accounting for 31, 29, and 15%, respectively, of the total integral flows for all paths. The flows through the sewage treatment and transportation components showed marked growth, with total integrated inputs plus outputs increasing to 3.7 and 5.2 times their 1996 values, respectively. Our results can help policymakers to locate the key nodes and pathways in an urban nitrogen metabolic system so they can monitor and manage these components of the system.

Outcomes of Multiple Listing for Adult Heart Transplantation in the United States: Analysis of OPTN Data From 2000 to 2013.

PubMed

Givens, Raymond C; Dardas, Todd; Clerkin, Kevin J; Restaino, Susan; Schulze, P Christian; Mancini, Donna M

2015-12-01

This study sought to assess the association of multiple listing with waitlist outcomes and post-heart transplant (HT) survival. HT candidates in the United States may register at multiple centers. Not all candidates have the resources and mobility needed for multiple listing; thus this policy may advantage wealthier and less sick patients. We identified 33,928 adult candidates for a first single-organ HT between January 1, 2000 and December 31, 2013 in the Organ Procurement and Transplantation Network database. We identified 679 multiple-listed (ML) candidates (2.0%) who were younger (median age, 53 years [interquartile range (IQR): 43 to 60 years] vs. 55 years [IQR: 45 to 61 years]; p < 0.0001), more often white (76.4% vs. 70.7%; p = 0.0010) and privately insured (65.5% vs. 56.3%; p < 0.0001), and lived in zip codes with higher median incomes (US$90,153 [IQR: US$25,471 to US$253,831] vs. US$68,986 [IQR: US$19,471 to US$219,702]; p = 0.0015). Likelihood of ML increased with the primary center's median waiting time. ML candidates had lower initial priority (39.0% 1A or 1B vs. 55.1%; p < 0.0001) and predicted 90-day waitlist mortality (2.9% [IQR: 2.3% to 4.7%] vs. 3.6% [IQR: 2.3% to 6.0]%; p < 0.0001), but were frequently upgraded at secondary centers (58.2% 1A/1B; p < 0.0001 vs. ML primary listing). ML candidates had a higher HT rate (74.4% vs. 70.2%; p = 0.0196) and lower waitlist mortality (8.1% vs. 12.2%; p = 0.0011). Compared with a propensity-matched cohort, the relative ML HT rate was 3.02 (95% confidence interval: 2.59 to 3.52; p < 0.0001). There were no post-HT survival differences. Multiple listing is a rational response to organ shortage but may advantage patients with the means to participate rather than the most medically needy. The multiple-listing policy should be overturned. Copyright © 2015 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.

An integrated GIS-based data model for multimodal urban public transportation analysis and management

NASA Astrophysics Data System (ADS)

Chen, Shaopei; Tan, Jianjun; Ray, C.; Claramunt, C.; Sun, Qinqin

2008-10-01

Diversity is one of the main characteristics of transportation data collected from multiple sources or formats, which can be extremely complex and disparate. Moreover, these multimodal transportation data are usually characterised by spatial and temporal properties. Multimodal transportation network data modelling involves both an engineering and research domain that has attracted the design of a number of spatio-temporal data models in the geographic information system (GIS). However, the application of these specific models to multimodal transportation network is still a challenging task. This research addresses this challenge from both integrated multimodal data organization and object-oriented modelling perspectives, that is, how a complex urban transportation network should be organized, represented and modeled appropriately when considering a multimodal point of view, and using object-oriented modelling method. We proposed an integrated GIS-based data model for multimodal urban transportation network that lays a foundation to enhance the multimodal transportation network analysis and management. This modelling method organizes and integrates multimodal transit network data, and supports multiple representations for spatio-temporal objects and relationship as both visual and graphic views. The data model is expressed by using a spatio-temporal object-oriented modelling method, i.e., the unified modelling language (UML) extended to spatial and temporal plug-in for visual languages (PVLs), which provides an essential support to the spatio-temporal data modelling for transportation GIS.

Twelve Tips for teaching medical professionalism at all levels of medical education.

PubMed

Al-Eraky, Mohamed Mostafa

2015-01-01

Review of studies published in medical education journals over the last decade reveals that teaching medical professionalism is essential, yet challenging. According to a recent Best Evidence in Medical Education (BEME) guide, there is no consensus on a theoretical or practical model to integrate the teaching of professionalism into medical education. The aim of this article is to outline a practical manual for teaching professionalism at all levels of medical education. Drawing from research literature and author's experience, Twelve Tips are listed and organised in four clusters with relevance to (1) the context, (2) the teachers, (3) the curriculum, and (4) the networking. With a better understanding of the guiding educational principles for teaching medical professionalism, medical educators will be able to teach one of the most challenging constructs in medical education.

Network Systems Technician.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Center on Education and Training for Employment.

This publication contains 17 subjects appropriate for use in a competency list for the occupation of network systems technician, 1 of 12 occupations within the business/computer technologies cluster. Each unit consists of a number of competencies; a list of competency builders is provided for each competency. Titles of the 17 units are as follows:…

Computer (PC/Network) Coordinator.

ERIC Educational Resources Information Center

Ohio State Univ., Columbus. Center on Education and Training for Employment.

This publication contains 22 subjects appropriate for use in a competency list for the occupation of computer (PC/network) coordinator, 1 of 12 occupations within the business/computer technologies cluster. Each unit consists of a number of competencies; a list of competency builders is provided for each competency. Titles of the 22 units are as…

High Energy Physics and Nuclear Physics Network Requirements

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dart, Eli; Bauerdick, Lothar; Bell, Greg

The Energy Sciences Network (ESnet) is the primary provider of network connectivity for the U.S. Department of Energy (DOE) Office of Science (SC), the single largest supporter of basic research in the physical sciences in the United States. In support of SC programs, ESnet regularly updates and refreshes its understanding of the networking requirements needed by instruments, facilities, scientists, and science programs that it serves. This focus has helped ESnet to be a highly successful enabler of scientific discovery for over 25 years. In August 2013, ESnet and the DOE SC Offices of High Energy Physics (HEP) and Nuclear Physicsmore » (NP) organized a review to characterize the networking requirements of the programs funded by the HEP and NP program offices. Several key findings resulted from the review. Among them: 1. The Large Hadron Collider?s ATLAS (A Toroidal LHC Apparatus) and CMS (Compact Muon Solenoid) experiments are adopting remote input/output (I/O) as a core component of their data analysis infrastructure. This will significantly increase their demands on the network from both a reliability perspective and a performance perspective. 2. The Large Hadron Collider (LHC) experiments (particularly ATLAS and CMS) are working to integrate network awareness into the workflow systems that manage the large number of daily analysis jobs (1 million analysis jobs per day for ATLAS), which are an integral part of the experiments. Collaboration with networking organizations such as ESnet, and the consumption of performance data (e.g., from perfSONAR [PERformance Service Oriented Network monitoring Architecture]) are critical to the success of these efforts. 3. The international aspects of HEP and NP collaborations continue to expand. This includes the LHC experiments, the Relativistic Heavy Ion Collider (RHIC) experiments, the Belle II Collaboration, the Large Synoptic Survey Telescope (LSST), and others. The international nature of these collaborations makes them heavily reliant on transoceanic connectivity, which is subject to longer term service disruptions than terrestrial connectivity. The network engineering aspects of undersea connectivity will continue to be a significant part of the planning, deployment, and operation of the data analysis infrastructure for HEP and NP experiments for the foreseeable future. Given their critical dependency on networking services, the experiments have expressed the need for tight integration (both technically and operationally) of the domestic and the transoceanic parts of the network infrastructure that supports the experiments. 4. The datasets associated with simulations continue to increase in size, and the need to move these datasets between analysis centers is placing ever-increasing demands on networks and on data management systems at the supercomputing centers. In addition, there is a need to harmonize cybersecurity practice with the data transfer performance requirements of the science. This report expands on these points, and addresses others as well. The report contains a findings section in addition to the text of the case studies discussed during the review.« less

Integrated communication and control systems. I - Analysis

NASA Technical Reports Server (NTRS)

Halevi, Yoram; Ray, Asok

1988-01-01

The paper presents the results of an ICCS analysis focusing on discrete-time control systems subject to time-varying delays. The present analytical technique is applicable to integrated dynamic systems such as those encountered in advanced aircraft, spacecraft, and the real-time control of robots and machine tools via a high-speed network within an autonomous manufacturing environment. The significance of data latency and missynchronization between individual system components in ICCS networks is discussed in view of the time-varying delays.

A Simplified Integrated Fish Culture Hydroponics System.

ERIC Educational Resources Information Center

Emberger, Gary

1991-01-01

Investigations that facilitate experimental design, the concept of replication, data analysis, and other aspects of scientific study are described. A list of materials, the recommended plants, and the directions for building the hydroponics unit are included. (KR)

Application of Information-Theoretic Data Mining Techniques in a National Ambulatory Practice Outcomes Research Network

PubMed Central

Wright, Adam; Ricciardi, Thomas N.; Zwick, Martin

2005-01-01

The Medical Quality Improvement Consortium data warehouse contains de-identified data on more than 3.6 million patients including their problem lists, test results, procedures and medication lists. This study uses reconstructability analysis, an information-theoretic data mining technique, on the MQIC data warehouse to empirically identify risk factors for various complications of diabetes including myocardial infarction and microalbuminuria. The risk factors identified match those risk factors identified in the literature, demonstrating the utility of the MQIC data warehouse for outcomes research, and RA as a technique for mining clinical data warehouses. PMID:16779156

Network portal: a database for storage, analysis and visualization of biological networks

PubMed Central

Turkarslan, Serdar; Wurtmann, Elisabeth J.; Wu, Wei-Ju; Jiang, Ning; Bare, J. Christopher; Foley, Karen; Reiss, David J.; Novichkov, Pavel; Baliga, Nitin S.

2014-01-01

The ease of generating high-throughput data has enabled investigations into organismal complexity at the systems level through the inference of networks of interactions among the various cellular components (genes, RNAs, proteins and metabolites). The wider scientific community, however, currently has limited access to tools for network inference, visualization and analysis because these tasks often require advanced computational knowledge and expensive computing resources. We have designed the network portal (http://networks.systemsbiology.net) to serve as a modular database for the integration of user uploaded and public data, with inference algorithms and tools for the storage, visualization and analysis of biological networks. The portal is fully integrated into the Gaggle framework to seamlessly exchange data with desktop and web applications and to allow the user to create, save and modify workspaces, and it includes social networking capabilities for collaborative projects. While the current release of the database contains networks for 13 prokaryotic organisms from diverse phylogenetic clades (4678 co-regulated gene modules, 3466 regulators and 9291 cis-regulatory motifs), it will be rapidly populated with prokaryotic and eukaryotic organisms as relevant data become available in public repositories and through user input. The modular architecture, simple data formats and open API support community development of the portal. PMID:24271392

Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks

PubMed Central

Harris, Daniel R.; Baus, Adam D.; Harper, Tamela J.; Jarrett, Traci D.; Pollard, Cecil R.; Talbert, Jeffery C.

2017-01-01

We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites. PMID:28261006

Using i2b2 to Bootstrap Rural Health Analytics and Learning Networks.

PubMed

Harris, Daniel R; Baus, Adam D; Harper, Tamela J; Jarrett, Traci D; Pollard, Cecil R; Talbert, Jeffery C

2016-08-01

We demonstrate that the open-source i2b2 (Informatics for Integrating Biology and the Bedside) data model can be used to bootstrap rural health analytics and learning networks. These networks promote communication and research initiatives by providing the infrastructure necessary for sharing data and insights across a group of healthcare and research partners. Data integration remains a crucial challenge in connecting rural healthcare sites with a common data sharing and learning network due to the lack of interoperability and standards within electronic health records. The i2b2 data model acts as a point of convergence for disparate data from multiple healthcare sites. A consistent and natural data model for healthcare data is essential for overcoming integration issues, but challenges such as those caused by weak data standardization must still be addressed. We describe our experience in the context of building the West Virginia/Kentucky Health Analytics and Learning Network, a collaborative, multi-state effort connecting rural healthcare sites.

A review of evidence of health benefit from artificial neural networks in medical intervention.

PubMed

Lisboa, P J G

2002-01-01

The purpose of this review is to assess the evidence of healthcare benefits involving the application of artificial neural networks to the clinical functions of diagnosis, prognosis and survival analysis, in the medical domains of oncology, critical care and cardiovascular medicine. The primary source of publications is PUBMED listings under Randomised Controlled Trials and Clinical Trials. The rĵle of neural networks is introduced within the context of advances in medical decision support arising from parallel developments in statistics and artificial intelligence. This is followed by a survey of published Randomised Controlled Trials and Clinical Trials, leading to recommendations for good practice in the design and evaluation of neural networks for use in medical intervention.

Integrated Seismological Network of Brazil: Key developments in technology.

NASA Astrophysics Data System (ADS)

Pirchiner, Marlon; Assumpção, Marcelo; Ferreira, Joaquim; França, George

2010-05-01

The Integrated Seismological Network of Brazil - BRASIS - will integrate the main Brazilian seismology groups in an extensive permanent broadband network with a (near) real-time acquisition system and automatic preliminary processing of epicenters and magnitudes. About 60 stations will cover the whole country to continuously monitor the seismic activity. Most stations will be operating by the end of 2010. Data will be received from remote stations at each research group and redistributed to all other groups. In addition to issuing a national catalog of earthquakes, each institution will make its own analysis and issue their own bulletins taking into account local and regional lithospheric structure. We chose the SEED format, seedlink and SeisComP as standard data format, exchange protocol and software framework for the network management, respectively. All different existing equipment (eg, Guralp/Scream, Geotech/CD1.1, RefTek/RTP, Quanterra/seedlink) will be integrated into the same system. We plan to provide: 1) improved station management through remote control, and indexes for quality control of acquired data, sending alerts to operators in critical cases. 2) automatic processing: picking, location with local and regional models and determination of magnitudes, issuing newsletters and alerts. 3) maintainence of an earthquakes catalog, and a waveforms database. 4) query tools and access to metadata, catalogs and waveform available to all researchers. In addition, the catalog of earthquakes and other seismological data will be available as layers in a Spatial Data Infrastructure with open source standards, providing new analysis capabilities to all geoscientists. Seiscomp3 has already been installed in two centers (UFRN and USP) with successful tests of Q330, Guralp, RefTek and Geotech plug-ins to the seedlink protocol. We will discuss the main difficulties of our project and the solutions adopted to improve the Brazilian seismological infrastructure.

Utilization of Concurrent Buffers to Facilitate Seamless Data Transition in Tactical Cellular Communications

DTIC Science & Technology

2015-09-01

INTENTIONALLY LEFT BLANK xiii LIST OF ACRONYMS AND ABBREVIATIONS 2G 2nd Generation 3G 3rd Generation 3GPP 3rd Generation Partnership Project 4G 4th...System (UMTS) is the standard that governs 3rd Generation ( 3G ) migration of Global Services for Mobile (GSM) networks. It defines packet-based...network may assist or mitigate. 14. SUBJECT TERMS IEEE, 802.21, Media Independent Handover, mobile , communications, cyber, tactical, buffer, cellular

Identifying Supervisory Control and Data Acquisition (SCADA) Systems on a Network via Remote Reconnaissance

DTIC Science & Technology

2006-09-01

and other forms of Internet research were used to confirm the relevance of the OUI to control system reconnaissance. I assigned a subjective level...equipment 4 = Confirmed with Internet research 5 = Suspected with Internet research OUI Organization Confidence Notes 00:00:0A Omron Tateisi...IP Vendor List 2 = Cross Referenced with IANA port list 3 = Confirmed with lab equipment 4 = Confirmed with Internet research 5 = Suspected with

A 40 GHz fully integrated circuit with a vector network analyzer and a coplanar-line-based detection area for circulating tumor cell analysis using 65 nm CMOS technology

NASA Astrophysics Data System (ADS)

Nakanishi, Taiki; Matsunaga, Maya; Kobayashi, Atsuki; Nakazato, Kazuo; Niitsu, Kiichi

2018-03-01

A 40-GHz fully integrated CMOS-based circuit for circulating tumor cells (CTC) analysis, consisting of an on-chip vector network analyzer (VNA) and a highly sensitive coplanar-line-based detection area is presented in this paper. In this work, we introduce a fully integrated architecture that eliminates unwanted parasitic effects. The proposed analyzer was designed using 65 nm CMOS technology, and SPICE and MWS simulations were used to validate its operation. The simulation confirmed that the proposed circuit can measure S-parameter shifts resulting from the addition of various types of tumor cells to the detection area, the data of which are provided in a previous study: the |S 21| values for HepG2, A549, and HEC-1-A cells are -0.683, -0.580, and -0.623 dB, respectively. Additionally, the measurement demonstrated an S-parameters reduction of -25.7% when a silicone resin was put on the circuit. Hence, the proposed system is expected to contribute to cancer diagnosis.

Evolution of a Patient Information Management System in a Local Area Network Environment at Loyola University of Chicago Medical Center

PubMed Central

Price, Ronald N; Chandrasekhar, Arcot J; Tamirisa, Balaji

1990-01-01

The Department of Medicine at Loyola University Medical Center (LUMC) of Chicago has implemented a local area network (LAN) based Patient Information Management System (PIMS) as part of its integrated departmental database management system. PIMS consists of related database applications encompassing demographic information, current medications, problem lists, clinical data, prior events, and on-line procedure results. Integration into the existing departmental database system permits PIMS to capture and manipulate data in other departmental applications. Standardization of clinical data is accomplished through three data tables that verify diagnosis codes, procedures codes and a standardized set of clinical data elements. The modularity of the system, coupled with standardized data formats, allowed the development of a Patient Information Protocol System (PIPS). PIPS, a userdefinable protocol processor, provides physicians with individualized data entry or review screens customized for their specific research protocols or practice habits. Physician feedback indicates that the PIMS/PIPS combination enhances their ability to collect and review specific patient information by filtering large amount of clinical data.

Structure and Connectivity Analysis of Financial Complex System Based on G-Causality Network

NASA Astrophysics Data System (ADS)

Xu, Chuan-Ming; Yan, Yan; Zhu, Xiao-Wu; Li, Xiao-Teng; Chen, Xiao-Song

2013-11-01

The recent financial crisis highlights the inherent weaknesses of the financial market. To explore the mechanism that maintains the financial market as a system, we study the interactions of U.S. financial market from the network perspective. Applied with conditional Granger causality network analysis, network density, in-degree and out-degree rankings are important indicators to analyze the conditional causal relationships among financial agents, and further to assess the stability of U.S. financial systems. It is found that the topological structure of G-causality network in U.S. financial market changed in different stages over the last decade, especially during the recent global financial crisis. Network density of the G-causality model is much higher during the period of 2007-2009 crisis stage, and it reaches the peak value in 2008, the most turbulent time in the crisis. Ranked by in-degrees and out-degrees, insurance companies are listed in the top of 68 financial institutions during the crisis. They act as the hubs which are more easily influenced by other financial institutions and simultaneously influence others during the global financial disturbance.

Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation

PubMed Central

Kwak, Doyeon

2017-01-01

It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks. PMID:28542367

Who collaborates and why: Assessment and diagnostic of governance network integration for salmon restoration in Puget Sound, USA.

PubMed

Sayles, Jesse S; Baggio, Jacopo A

2017-01-15

Governance silos are settings in which different organizations work in isolation and avoid sharing information and strategies. Siloes are a fundamental challenge for environmental planning and problem solving, which generally requires collaboration. Siloes can be overcome by creating governance networks. Studying the structure and function of these networks is important for understanding how to create institutional arrangements that can respond to the biophysical dynamics of a specific natural resource system (i.e., social-ecological, or institutional fit). Using the case of salmon restoration in a sub-basin of Puget Sound, USA, we assess network integration, considering three different reasons for network collaborations (i.e., mandated, funded, and shared interest relationships) and analyze how these different collaboration types relate to productivity based on practitioner's assessments. We also illustrate how specific and targeted network interventions might enhance the network. To do so, we use a mixed methods approach that combines quantitative social network analysis (SNA) and qualitative interview analysis. Overall, the sub-basin's governance network is fairly well integrated, but several concerning gaps exist. Funded, mandated, and shared interest relationships lead to different network patterns. Mandated relationships are associated with lower productivity than shared interest relationships, highlighting the benefit of genuine collaboration in collaborative watershed governance. Lastly, quantitative and qualitative data comparisons strengthen recent calls to incorporate geographic space and the role of individual actors versus organizational culture into natural resource governance research using SNA. Copyright © 2016 Elsevier Ltd. All rights reserved.

Understanding the process of social network evolution: Online-offline integrated analysis of social tie formation.

PubMed

Kwak, Doyeon; Kim, Wonjoon

2017-01-01

It is important to consider the interweaving nature of online and offline social networks when we examine social network evolution. However, it is difficult to find any research that examines the process of social tie formation from an integrated perspective. In our study, we quantitatively measure offline interactions and examine the corresponding evolution of online social network in order to understand the significance of interrelationship between online and offline social factors in generating social ties. We analyze the radio signal strength indicator sensor data from a series of social events to understand offline interactions among the participants and measure the structural attributes of their existing online Facebook social networks. By monitoring the changes in their online social networks before and after offline interactions in a series of social events, we verify that the ability to develop an offline interaction into an online friendship is tied to the number of social connections that participants previously had, while the presence of shared mutual friends between a pair of participants disrupts potential new connections within the pre-designed offline social events. Thus, while our integrative approach enables us to confirm the theory of preferential attachment in the process of network formation, the common neighbor theory is not supported. Our dual-dimensional network analysis allows us to observe the actual process of social network evolution rather than to make predictions based on the assumption of self-organizing networks.

Meshfree Modeling of Munitions Penetration in Soils

DTIC Science & Technology

2017-04-01

discretization ...................... 8 Figure 2. Nodal smoothing domain for the modified stabilized nonconforming nodal integration...projectile ............................................................................................... 36 Figure 17. Discretization for the...List of Acronyms DEM: discrete element methods FEM: finite element methods MSNNI: modified stabilized nonconforming nodal integration RK

SiGe BiCMOS manufacturing platform for mmWave applications

NASA Astrophysics Data System (ADS)

Kar-Roy, Arjun; Howard, David; Preisler, Edward; Racanelli, Marco; Chaudhry, Samir; Blaschke, Volker

2010-10-01

TowerJazz offers high volume manufacturable commercial SiGe BiCMOS technology platforms to address the mmWave market. In this paper, first, the SiGe BiCMOS process technology platforms such as SBC18 and SBC13 are described. These manufacturing platforms integrate 200 GHz fT/fMAX SiGe NPN with deep trench isolation into 0.18μm and 0.13μm node CMOS processes along with high density 5.6fF/μm2 stacked MIM capacitors, high value polysilicon resistors, high-Q metal resistors, lateral PNP transistors, and triple well isolation using deep n-well for mixed-signal integration, and, multiple varactors and compact high-Q inductors for RF needs. Second, design enablement tools that maximize performance and lowers costs and time to market such as scalable PSP and HICUM models, statistical and Xsigma models, reliability modeling tools, process control model tools, inductor toolbox and transmission line models are described. Finally, demonstrations in silicon for mmWave applications in the areas of optical networking, mobile broadband, phased array radar, collision avoidance radar and W-band imaging are listed.

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

PubMed Central

Bersanelli, Matteo; Mosca, Ettore; Remondini, Daniel; Castellani, Gastone; Milanesi, Luciano

2016-01-01

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD. PMID:27731320

Fuzzy Logic based Handoff Latency Reduction Mechanism in Layer 2 of Heterogeneous Mobile IPv6 Networks

NASA Astrophysics Data System (ADS)

Anwar, Farhat; Masud, Mosharrof H.; Latif, Suhaimi A.

2013-12-01

Mobile IPv6 (MIPv6) is one of the pioneer standards that support mobility in IPv6 environment. It has been designed to support different types of technologies for providing seamless communications in next generation network. However, MIPv6 and subsequent standards have some limitations due to its handoff latency. In this paper, a fuzzy logic based mechanism is proposed to reduce the handoff latency of MIPv6 for Layer 2 (L2) by scanning the Access Points (APs) while the Mobile Node (MN) is moving among different APs. Handoff latency occurs when the MN switches from one AP to another in L2. Heterogeneous network is considered in this research in order to reduce the delays in L2. Received Signal Strength Indicator (RSSI) and velocity of the MN are considered as the input of fuzzy logic technique. This technique helps the MN to measure optimum signal quality from APs for the speedy mobile node based on fuzzy logic input rules and makes a list of interfaces. A suitable interface from the list of available interfaces can be selected like WiFi, WiMAX or GSM. Simulation results show 55% handoff latency reduction and 50% packet loss improvement in L2 compared to standard to MIPv6.

Visual analysis and exploration of complex corporate shareholder networks

NASA Astrophysics Data System (ADS)

Tekušová, Tatiana; Kohlhammer, Jörn

2008-01-01

The analysis of large corporate shareholder network structures is an important task in corporate governance, in financing, and in financial investment domains. In a modern economy, large structures of cross-corporation, cross-border shareholder relationships exist, forming complex networks. These networks are often difficult to analyze with traditional approaches. An efficient visualization of the networks helps to reveal the interdependent shareholding formations and the controlling patterns. In this paper, we propose an effective visualization tool that supports the financial analyst in understanding complex shareholding networks. We develop an interactive visual analysis system by combining state-of-the-art visualization technologies with economic analysis methods. Our system is capable to reveal patterns in large corporate shareholder networks, allows the visual identification of the ultimate shareholders, and supports the visual analysis of integrated cash flow and control rights. We apply our system on an extensive real-world database of shareholder relationships, showing its usefulness for effective visual analysis.

The complex genetics of gait speed: genome-wide meta-analysis approach

PubMed Central

Lunetta, Kathryn L.; Smith, Jennifer A.; Eicher, John D.; Vered, Rotem; Deelen, Joris; Arnold, Alice M.; Buchman, Aron S.; Tanaka, Toshiko; Faul, Jessica D.; Nethander, Maria; Fornage, Myriam; Adams, Hieab H.; Matteini, Amy M.; Callisaya, Michele L.; Smith, Albert V.; Yu, Lei; De Jager, Philip L.; Evans, Denis A.; Gudnason, Vilmundur; Hofman, Albert; Pattie, Alison; Corley, Janie; Launer, Lenore J.; Knopman, Davis S.; Parimi, Neeta; Turner, Stephen T.; Bandinelli, Stefania; Beekman, Marian; Gutman, Danielle; Sharvit, Lital; Mooijaart, Simon P.; Liewald, David C.; Houwing-Duistermaat, Jeanine J.; Ohlsson, Claes; Moed, Matthijs; Verlinden, Vincent J.; Mellström, Dan; van der Geest, Jos N.; Karlsson, Magnus; Hernandez, Dena; McWhirter, Rebekah; Liu, Yongmei; Thomson, Russell; Tranah, Gregory J.; Uitterlinden, Andre G.; Weir, David R.; Zhao, Wei; Starr, John M.; Johnson, Andrew D.; Ikram, M. Arfan; Bennett, David A.; Cummings, Steven R.; Deary, Ian J.; Harris, Tamara B.; Kardia, Sharon L. R.; Mosley, Thomas H.; Srikanth, Velandai K.; Windham, Beverly G.; Newman, Ann B.; Walston, Jeremy D.; Davies, Gail; Evans, Daniel S.; Slagboom, Eline P.; Ferrucci, Luigi; Kiel, Douglas P.; Murabito, Joanne M.; Atzmon, Gil

2017-01-01

Emerging evidence suggests that the basis for variation in late-life mobility is attributable, in part, to genetic factors, which may become increasingly important with age. Our objective was to systematically assess the contribution of genetic variation to gait speed in older individuals. We conducted a meta-analysis of gait speed GWASs in 31,478 older adults from 17 cohorts of the CHARGE consortium, and validated our results in 2,588 older adults from 4 independent studies. We followed our initial discoveries with network and eQTL analysis of candidate signals in tissues. The meta-analysis resulted in a list of 536 suggestive genome wide significant SNPs in or near 69 genes. Further interrogation with Pathway Analysis placed gait speed as a polygenic complex trait in five major networks. Subsequent eQTL analysis revealed several SNPs significantly associated with the expression of PRSS16, WDSUB1 and PTPRT, which in addition to the meta-analysis and pathway suggested that genetic effects on gait speed may occur through synaptic function and neuronal development pathways. No genome-wide significant signals for gait speed were identified from this moderately large sample of older adults, suggesting that more refined physical function phenotypes will be needed to identify the genetic basis of gait speed in aging. PMID:28077804

Interconnection network architectures based on integrated orbital angular momentum emitters

NASA Astrophysics Data System (ADS)

Scaffardi, Mirco; Zhang, Ning; Malik, Muhammad Nouman; Lazzeri, Emma; Klitis, Charalambos; Lavery, Martin; Sorel, Marc; Bogoni, Antonella

2018-02-01

Novel architectures for two-layer interconnection networks based on concentric OAM emitters are presented. A scalability analysis is done in terms of devices characteristics, power budget and optical signal to noise ratio by exploiting experimentally measured parameters. The analysis shows that by exploiting optical amplifications, the proposed interconnection networks can support a number of ports higher than 100. The OAM crosstalk induced-penalty, evaluated through an experimental characterization, do not significantly affect the interconnection network performance.

A multi-tissue type genome-scale metabolic network for analysis of whole-body systems physiology

PubMed Central

2011-01-01

Background Genome-scale metabolic reconstructions provide a biologically meaningful mechanistic basis for the genotype-phenotype relationship. The global human metabolic network, termed Recon 1, has recently been reconstructed allowing the systems analysis of human metabolic physiology and pathology. Utilizing high-throughput data, Recon 1 has recently been tailored to different cells and tissues, including the liver, kidney, brain, and alveolar macrophage. These models have shown utility in the study of systems medicine. However, no integrated analysis between human tissues has been done. Results To describe tissue-specific functions, Recon 1 was tailored to describe metabolism in three human cells: adipocytes, hepatocytes, and myocytes. These cell-specific networks were manually curated and validated based on known cellular metabolic functions. To study intercellular interactions, a novel multi-tissue type modeling approach was developed to integrate the metabolic functions for the three cell types, and subsequently used to simulate known integrated metabolic cycles. In addition, the multi-tissue model was used to study diabetes: a pathology with systemic properties. High-throughput data was integrated with the network to determine differential metabolic activity between obese and type II obese gastric bypass patients in a whole-body context. Conclusion The multi-tissue type modeling approach presented provides a platform to study integrated metabolic states. As more cell and tissue-specific models are released, it is critical to develop a framework in which to study their interdependencies. PMID:22041191

Leveraging multiple gene networks to prioritize GWAS candidate genes via network representation learning.

PubMed

Wu, Mengmeng; Zeng, Wanwen; Liu, Wenqiang; Lv, Hairong; Chen, Ting; Jiang, Rui

2018-06-03

Genome-wide association studies (GWAS) have successfully discovered a number of disease-associated genetic variants in the past decade, providing an unprecedented opportunity for deciphering genetic basis of human inherited diseases. However, it is still a challenging task to extract biological knowledge from the GWAS data, due to such issues as missing heritability and weak interpretability. Indeed, the fact that the majority of discovered loci fall into noncoding regions without clear links to genes has been preventing the characterization of their functions and appealing for a sophisticated approach to bridge genetic and genomic studies. Towards this problem, network-based prioritization of candidate genes, which performs integrated analysis of gene networks with GWAS data, has emerged as a promising direction and attracted much attention. However, most existing methods overlook the sparse and noisy properties of gene networks and thus may lead to suboptimal performance. Motivated by this understanding, we proposed a novel method called REGENT for integrating multiple gene networks with GWAS data to prioritize candidate genes for complex diseases. We leveraged a technique called the network representation learning to embed a gene network into a compact and robust feature space, and then designed a hierarchical statistical model to integrate features of multiple gene networks with GWAS data for the effective inference of genes associated with a disease of interest. We applied our method to six complex diseases and demonstrated the superior performance of REGENT over existing approaches in recovering known disease-associated genes. We further conducted a pathway analysis and showed that the ability of REGENT to discover disease-associated pathways. We expect to see applications of our method to a broad spectrum of diseases for post-GWAS analysis. REGENT is freely available at https://github.com/wmmthu/REGENT. Copyright © 2018 Elsevier Inc. All rights reserved.

76 FR 41135 - 2-Propenoic acid, 2-methyl-, phenylmethyl ester, polymer with 2-propenoic acid and sodium 2...

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-13

... a finite tolerance is not necessary to ensure that there is a reasonable certainty that no harm will... integral part of its composition the atomic elements carbon, hydrogen, and oxygen. 3. The polymer does not contain as an integral part of its composition, except as impurities, any element other than those listed...

Integration of Multiple UAVs for Collaborative ISR Missions in an Urban Environment

DTIC Science & Technology

2012-09-01

URBAN ENVIRONMENT UAVS .............................3  1.  Qube UAS ......................................4  2.  SQ-4...93  INITIAL DISTRIBUTION LIST ...................................97  ix LIST OF FIGURES   Qube UAS by Aerovironment. From [7...laboratory setup. From [31].....................47    Sonar sensor....................................49 Figure 25.   Reflectors on the UAV

Variations in Social Network Type Membership Among Older African Americans, Caribbean Blacks, and Non-Hispanic Whites

PubMed Central

2017-01-01

Abstract Objectives: This study examined race differences in the probability of belonging to a specific social network typology of family, friends, and church members. Method: Samples of African Americans, Caribbean blacks, and non-Hispanic whites aged 55+ were drawn from the National Survey of American Life. Typology indicators related to social integration and negative interactions with family, friendship, and church networks were used. Latent class analysis was used to identify typologies, and latent class multinomial logistic regression was used to assess the influence of race, and interactions between race and age, and race and education on typology membership. Results: Four network typologies were identified: optimal (high social integration, low negative interaction), family-centered (high social integration within primarily the extended family network, low negative interaction), strained (low social integration, high negative interaction), and ambivalent (high social integration and high negative interaction). Findings for race and age and race and education interactions indicated that the effects of education and age on typology membership varied by race. Discussion: Overall, the findings demonstrate how race interacts with age and education to influence the probability of belonging to particular network types. A better understanding of the influence of race, education, and age on social network typologies will inform future research and theoretical developments in this area. PMID:28329871

14 CFR 121.909 - Approval of Advanced Qualification Program.

Code of Federal Regulations, 2010 CFR

2010-01-01

... methodology must incorporate a thorough analysis of the certificate holder's operations, aircraft, line environment and job functions. All AQP qualification and continuing qualification curriculums must integrate.... (ii) Initial job task listing. (iii) Instructional systems development methodology. (iv) Qualification...

Genomic analyses identify molecular subtypes of pancreatic cancer.

PubMed

Bailey, Peter; Chang, David K; Nones, Katia; Johns, Amber L; Patch, Ann-Marie; Gingras, Marie-Claude; Miller, David K; Christ, Angelika N; Bruxner, Tim J C; Quinn, Michael C; Nourse, Craig; Murtaugh, L Charles; Harliwong, Ivon; Idrisoglu, Senel; Manning, Suzanne; Nourbakhsh, Ehsan; Wani, Shivangi; Fink, Lynn; Holmes, Oliver; Chin, Venessa; Anderson, Matthew J; Kazakoff, Stephen; Leonard, Conrad; Newell, Felicity; Waddell, Nick; Wood, Scott; Xu, Qinying; Wilson, Peter J; Cloonan, Nicole; Kassahn, Karin S; Taylor, Darrin; Quek, Kelly; Robertson, Alan; Pantano, Lorena; Mincarelli, Laura; Sanchez, Luis N; Evers, Lisa; Wu, Jianmin; Pinese, Mark; Cowley, Mark J; Jones, Marc D; Colvin, Emily K; Nagrial, Adnan M; Humphrey, Emily S; Chantrill, Lorraine A; Mawson, Amanda; Humphris, Jeremy; Chou, Angela; Pajic, Marina; Scarlett, Christopher J; Pinho, Andreia V; Giry-Laterriere, Marc; Rooman, Ilse; Samra, Jaswinder S; Kench, James G; Lovell, Jessica A; Merrett, Neil D; Toon, Christopher W; Epari, Krishna; Nguyen, Nam Q; Barbour, Andrew; Zeps, Nikolajs; Moran-Jones, Kim; Jamieson, Nigel B; Graham, Janet S; Duthie, Fraser; Oien, Karin; Hair, Jane; Grützmann, Robert; Maitra, Anirban; Iacobuzio-Donahue, Christine A; Wolfgang, Christopher L; Morgan, Richard A; Lawlor, Rita T; Corbo, Vincenzo; Bassi, Claudio; Rusev, Borislav; Capelli, Paola; Salvia, Roberto; Tortora, Giampaolo; Mukhopadhyay, Debabrata; Petersen, Gloria M; Munzy, Donna M; Fisher, William E; Karim, Saadia A; Eshleman, James R; Hruban, Ralph H; Pilarsky, Christian; Morton, Jennifer P; Sansom, Owen J; Scarpa, Aldo; Musgrove, Elizabeth A; Bailey, Ulla-Maja Hagbo; Hofmann, Oliver; Sutherland, Robert L; Wheeler, David A; Gill, Anthony J; Gibbs, Richard A; Pearson, John V; Waddell, Nicola; Biankin, Andrew V; Grimmond, Sean M

2016-03-03

Integrated genomic analysis of 456 pancreatic ductal adenocarcinomas identified 32 recurrently mutated genes that aggregate into 10 pathways: KRAS, TGF-β, WNT, NOTCH, ROBO/SLIT signalling, G1/S transition, SWI-SNF, chromatin modification, DNA repair and RNA processing. Expression analysis defined 4 subtypes: (1) squamous; (2) pancreatic progenitor; (3) immunogenic; and (4) aberrantly differentiated endocrine exocrine (ADEX) that correlate with histopathological characteristics. Squamous tumours are enriched for TP53 and KDM6A mutations, upregulation of the TP63∆N transcriptional network, hypermethylation of pancreatic endodermal cell-fate determining genes and have a poor prognosis. Pancreatic progenitor tumours preferentially express genes involved in early pancreatic development (FOXA2/3, PDX1 and MNX1). ADEX tumours displayed upregulation of genes that regulate networks involved in KRAS activation, exocrine (NR5A2 and RBPJL), and endocrine differentiation (NEUROD1 and NKX2-2). Immunogenic tumours contained upregulated immune networks including pathways involved in acquired immune suppression. These data infer differences in the molecular evolution of pancreatic cancer subtypes and identify opportunities for therapeutic development.

Multiproteomic and Transcriptomic Analysis of Oncogenic β-Catenin Molecular Networks.

PubMed

Ewing, Rob M; Song, Jing; Gokulrangan, Giridharan; Bai, Sheldon; Bowler, Emily H; Bolton, Rachel; Skipp, Paul; Wang, Yihua; Wang, Zhenghe

2018-06-01

The dysregulation of Wnt signaling is a frequent occurrence in many different cancers. Oncogenic mutations of CTNNB1/β-catenin, the key nuclear effector of canonical Wnt signaling, lead to the accumulation and stabilization of β-catenin protein with diverse effects in cancer cells. Although the transcriptional response to Wnt/β-catenin signaling activation has been widely studied, an integrated understanding of the effects of oncogenic β-catenin on molecular networks is lacking. We used affinity-purification mass spectrometry (AP-MS), label-free liquid chromatography-tandem mass spectrometry, and RNA-Seq to compare protein-protein interactions, protein expression, and gene expression in colorectal cancer cells expressing mutant (oncogenic) or wild-type β-catenin. We generate an integrated molecular network and use it to identify novel protein modules that are associated with mutant or wild-type β-catenin. We identify a DNA methyltransferase I associated subnetwork that is enriched in cells with mutant β-catenin and a subnetwork enriched in wild-type cells associated with the CDKN2A tumor suppressor, linking these processes to the transformation of colorectal cancer cells through oncogenic β-catenin signaling. In summary, multiomics analysis of a defined colorectal cancer cell model provides a significantly more comprehensive identification of functional molecular networks associated with oncogenic β-catenin signaling.

Mechanics of the Cell

NASA Astrophysics Data System (ADS)

Boal, David

2012-01-01

Preface; List of symbols; 1. Introduction to the cell; 2. Soft materials and fluids; Part I. Rods and Ropes: 3. Polymers; 4. Complex filaments; 5. Two-dimensional networks; 6. Three-dimensional networks; Part II. Membranes: 7. Biomembranes; 8. Membrane undulations; 9. Intermembrane and electrostatic forces; Part III. The Whole Cell: 10. Structure of the simplest cells; 11. Dynamic filaments; 12. Growth and division; 13. Signals and switches; Appendixes; Glossary; References; Index.

St. Louis Regional Library Network Manuals: Delivery System Manual, INFO-PASS Manual, Interlibrary Loan Protocol, Procedures and Policies Manual.

ERIC Educational Resources Information Center

Saint Louis Regional Library Network, MO.

Included in this set of manuals are: (1) guidelines for document delivery to member libraries within the St. Louis Regional Library Network (SLRLN) in which eligible materials are described, addressing and packing are outlined, routing and deliveries are discussed, and a list of delivery system participants is provided; (2) a descriptive guide to…

VizieR Online Data Catalog: Complex network for solar active regions (Daei+, 2017)

NASA Astrophysics Data System (ADS)

Daei, F.; Safari, H.; Dadashi, N.

2018-03-01

The solar monitor (www.solarmonitor.org) records the solar data observed by several solar space observatories and missions (e.g., GOES, GONG, ACE, STEREO, SDO, etc.). 4227 solar active regions (ARs) during 1999 January 1 to 2017 April 14 used for building the AR network are listed in table 1. See section 2 for further details. (1 data file).

Training Knowledge and Skills for the Networked Battlefield

DTIC Science & Technology

2010-09-13

Healy, 2002). Participated were required to spell lists of spoken French words in a pretest , seeding phase, posttest , and 2-week retention test. The...REPORT Final Report, Army Research Office Grant W911NF-05-1-0153, Multidisciplinary University Research Initiative, Training Knowledge and Skills for...the Networked Battlefield 14. ABSTRACT 16. SECURITY CLASSIFICATION OF: The goal of our research , which has been supported by multidisciplinary

Pathway analysis of high-throughput biological data within a Bayesian network framework.

PubMed

Isci, Senol; Ozturk, Cengizhan; Jones, Jon; Otu, Hasan H

2011-06-15

Most current approaches to high-throughput biological data (HTBD) analysis either perform individual gene/protein analysis or, gene/protein set enrichment analysis for a list of biologically relevant molecules. Bayesian Networks (BNs) capture linear and non-linear interactions, handle stochastic events accounting for noise, and focus on local interactions, which can be related to causal inference. Here, we describe for the first time an algorithm that models biological pathways as BNs and identifies pathways that best explain given HTBD by scoring fitness of each network. Proposed method takes into account the connectivity and relatedness between nodes of the pathway through factoring pathway topology in its model. Our simulations using synthetic data demonstrated robustness of our approach. We tested proposed method, Bayesian Pathway Analysis (BPA), on human microarray data regarding renal cell carcinoma (RCC) and compared our results with gene set enrichment analysis. BPA was able to find broader and more specific pathways related to RCC. Accompanying BPA software (BPAS) package is freely available for academic use at http://bumil.boun.edu.tr/bpa.

A systems biology approach to the global analysis of transcription factors in colorectal cancer.

PubMed

Pradhan, Meeta P; Prasad, Nagendra K A; Palakal, Mathew J

2012-08-01

Biological entities do not perform in isolation, and often, it is the nature and degree of interactions among numerous biological entities which ultimately determines any final outcome. Hence, experimental data on any single biological entity can be of limited value when considered only in isolation. To address this, we propose that augmenting individual entity data with the literature will not only better define the entity's own significance but also uncover relationships with novel biological entities.To test this notion, we developed a comprehensive text mining and computational methodology that focused on discovering new targets of one class of molecular entities, transcription factors (TF), within one particular disease, colorectal cancer (CRC). We used 39 molecular entities known to be associated with CRC along with six colorectal cancer terms as the bait list, or list of search terms, for mining the biomedical literature to identify CRC-specific genes and proteins. Using the literature-mined data, we constructed a global TF interaction network for CRC. We then developed a multi-level, multi-parametric methodology to identify TFs to CRC. The small bait list, when augmented with literature-mined data, identified a large number of biological entities associated with CRC. The relative importance of these TF and their associated modules was identified using functional and topological features. Additional validation of these highly-ranked TF using the literature strengthened our findings. Some of the novel TF that we identified were: SLUG, RUNX1, IRF1, HIF1A, ATF-2, ABL1, ELK-1 and GATA-1. Some of these TFs are associated with functional modules in known pathways of CRC, including the Beta-catenin/development, immune response, transcription, and DNA damage pathways. Our methodology of using text mining data and a multi-level, multi-parameter scoring technique was able to identify both known and novel TF that have roles in CRC. Starting with just one TF (SMAD3) in the bait list, the literature mining process identified an additional 116 CRC-associated TFs. Our network-based analysis showed that these TFs all belonged to any of 13 major functional groups that are known to play important roles in CRC. Among these identified TFs, we obtained a novel six-node module consisting of ATF2-P53-JNK1-ELK1-EPHB2-HIF1A, from which the novel JNK1-ELK1 association could potentially be a significant marker for CRC.

Effects of amyloid and small vessel disease on white matter network disruption.

PubMed

Kim, Hee Jin; Im, Kiho; Kwon, Hunki; Lee, Jong Min; Ye, Byoung Seok; Kim, Yeo Jin; Cho, Hanna; Choe, Yearn Seong; Lee, Kyung Han; Kim, Sung Tae; Kim, Jae Seung; Lee, Jae Hong; Na, Duk L; Seo, Sang Won

2015-01-01

There is growing evidence that the human brain is a large scale complex network. The structural network is reported to be disrupted in cognitively impaired patients. However, there have been few studies evaluating the effects of amyloid and small vessel disease (SVD) markers, the common causes of cognitive impairment, on structural networks. Thus, we evaluated the association between amyloid and SVD burdens and structural networks using diffusion tensor imaging (DTI). Furthermore, we determined if network parameters predict cognitive impairments. Graph theoretical analysis was applied to DTI data from 232 cognitively impaired patients with varying degrees of amyloid and SVD burdens. All patients underwent Pittsburgh compound-B (PiB) PET to detect amyloid burden, MRI to detect markers of SVD, including the volume of white matter hyperintensities and the number of lacunes, and detailed neuropsychological testing. The whole-brain network was assessed by network parameters of integration (shortest path length, global efficiency) and segregation (clustering coefficient, transitivity, modularity). PiB retention ratio was not associated with any white matter network parameters. Greater white matter hyperintensity volumes or lacunae numbers were significantly associated with decreased network integration (increased shortest path length, decreased global efficiency) and increased network segregation (increased clustering coefficient, increased transitivity, increased modularity). Decreased network integration or increased network segregation were associated with poor performances in attention, language, visuospatial, memory, and frontal-executive functions. Our results suggest that SVD alters white matter network integration and segregation, which further predicts cognitive dysfunction.

A Qualitative Investigation of Practicing Psychologists' Attitudes Toward Research-Informed Practice: Implications for Dissemination Strategies

PubMed Central

Stewart, Rebecca E.; Stirman, Shannon Wiltsey; Chambless, Dianne L.

2012-01-01

This article presents the results of a qualitative analysis of interviews with 25 psychologists in independent practice, investigating everyday treatment decisions and attitudes about treatment outcome research and empirically supported treatments (ESTs). Clinicians noted positive aspects about treatment outcome research, such as being interested in what works. However, they had misgivings about the application of controlled research findings to their practices, were skeptical about using manualized protocols, and expressed concern that nonpsychologists would use EST lists to dictate practice. Clinicians reported practicing in an eclectic framework, and many reported including cognitive-behavioral elements in their practice. To improve their practice, they reported valuing clinical experience, peer networks, practitioner-oriented books, and continuing education when it was not too basic. Time and financial barriers concerned nearly all participants. Clinicians suggested they might be interested in ESTs if they could integrate them into their current frameworks, and if resources for learning ESTs were improved. PMID:22654246

Network Connectedness, Sense of Community, and Risk Perception of Climate Change Professionals in the Pacific Islands Region

NASA Astrophysics Data System (ADS)

Corlew, L. K.; Keener, V. W.; Finucane, M.

2013-12-01

The Pacific Regional Integrated Sciences and Assessments (Pacific RISA) Program conducted social network analysis research of climate change professionals (broadly defined) who are from or work in Hawaii and the U.S.-Affiliated Pacific Islands (USAPI) region. This study is supported by the National Oceanic and Atmospheric Administration (NOAA) and the Pacific Islands Climate Science Center (PICSC) to address an identified need for a resource that quantifies the region's collaborative network of climate change professionals, and that supports the further development of cross-regional and inter-sectoral collaborations for future research and adaptation activities. A survey was distributed to nearly 1,200 people who are from and/or work in climate change related fields in the region. The Part One Survey questions (not confidential) created a preferential attachment network by listing major players in Hawaii and the USAPI, with additional open fields to identify important contacts in the greater professional network. Participants (n=340) identified 975 network contacts and frequency of communications (weekly, monthly, seasonally, yearly, at least once ever). Part Two Survey questions (confidential, n=302) explored climate change risk perceptions, Psychological Sense of Community (PSOC), sense of control over climate change impacts, sense of responsibility to act, policy beliefs and preferences regarding climate change actions, concern and optimism scales about specific impacts, and demographic information. Graphical representations of the professional network are being developed for release in September 2013 as a free online tool to promote and assist collaboration building among climate professionals in the region. The graphs are partitioned according to network 'hubs' (high centrality), participant location, and profession to clearly identify network strengths and opportunities for future collaborations across spatial and professional boundaries. For additional analyses, scores are assigned for participant degree centrality, betweenness centrality, and Eigenvector centrality from the Part One Survey, as well as PSOC, control, responsibility, risk perceptions, concern, optimism, and policy preferences from the Part Two Survey. Statistical interaction analyses explore factors motivating connectedness within the network, as well as climate change research and adaptation needs and priorities of participants.

Voice/Data Integration in Mobile Radio Networks: Overview and Future Research Directions

DTIC Science & Technology

1989-09-30

degradation in interactive speech when delays are less than about 300 ms (Gold 1977; Gitman and Frank, 1978). When delays are larger (between 300 ms and 1.5...222-267. Gitman , 1. and H. Frank (1978), "Economic Analysis of Integrated Voice and Data Networks: A Case Study," Proc. IEEE 66 1549-1570. Glynn, P.W

Remaking memories: Reconsolidation updates positively motivated spatial memory in rats

PubMed Central

Jones, Bethany; Bukoski, Elizabeth; Nadel, Lynn; Fellous, Jean-Marc

2012-01-01

There is strong evidence that reactivation of a memory returns it to a labile state, initiating a restabilization process termed reconsolidation, which allows for updating of the memory. In this study we investigated reactivation-dependent updating using a new positively motivated spatial task in rodents that was designed specifically to model a human list-learning paradigm. On Day 1, rats were trained to run to three feeders (List 1) for rewards. On Day 2, rats were trained to run to three different feeders (List 2) in either the same (Reminder condition) or a different (No Reminder condition) experimental context than on Day 1. On Day 3, rats were cued to recall List 1. Rats in the Reminder condition made significantly more visits to List 2 feeders (intrusions) during List 1 recall than rats in the No Reminder condition, indicating that the reminder triggered reactivation and allowed integration of List 2 items into List 1. This reminder effect was selective for the reactivated List 1 memory, as no intrusions occurred when List 2 was recalled on Day 3. No intrusions occurred when retrieval took place in a different context from the one used at encoding, indicating that the expression of the updated memory is dependent upon the retrieval context. Finally, the level of intrusions was highest when retrieval took place immediately after List 2 learning, and generally declined when retrieval occurred 1–4 h later, indicating that the List 2 memory competed with short-term retrieval of List 1. These results demonstrate the dynamic nature of memory over time and the impact of environmental context at different stages of memory processing. PMID:22345494

Remaking memories: reconsolidation updates positively motivated spatial memory in rats.

PubMed

Jones, Bethany; Bukoski, Elizabeth; Nadel, Lynn; Fellous, Jean-Marc

2012-02-17

There is strong evidence that reactivation of a memory returns it to a labile state, initiating a restabilization process termed reconsolidation, which allows for updating of the memory. In this study we investigated reactivation-dependent updating using a new positively motivated spatial task in rodents that was designed specifically to model a human list-learning paradigm. On Day 1, rats were trained to run to three feeders (List 1) for rewards. On Day 2, rats were trained to run to three different feeders (List 2) in either the same (Reminder condition) or a different (No Reminder condition) experimental context than on Day 1. On Day 3, rats were cued to recall List 1. Rats in the Reminder condition made significantly more visits to List 2 feeders (intrusions) during List 1 recall than rats in the No Reminder condition, indicating that the reminder triggered reactivation and allowed integration of List 2 items into List 1. This reminder effect was selective for the reactivated List 1 memory, as no intrusions occurred when List 2 was recalled on Day 3. No intrusions occurred when retrieval took place in a different context from the one used at encoding, indicating that the expression of the updated memory is dependent upon the retrieval context. Finally, the level of intrusions was highest when retrieval took place immediately after List 2 learning, and generally declined when retrieval occurred 1-4 h later, indicating that the List 2 memory competed with short-term retrieval of List 1. These results demonstrate the dynamic nature of memory over time and the impact of environmental context at different stages of memory processing.

Topological analysis of metabolic networks integrating co-segregating transcriptomes and metabolomes in type 2 diabetic rat congenic series.

PubMed

Dumas, Marc-Emmanuel; Domange, Céline; Calderari, Sophie; Martínez, Andrea Rodríguez; Ayala, Rafael; Wilder, Steven P; Suárez-Zamorano, Nicolas; Collins, Stephan C; Wallis, Robert H; Gu, Quan; Wang, Yulan; Hue, Christophe; Otto, Georg W; Argoud, Karène; Navratil, Vincent; Mitchell, Steve C; Lindon, John C; Holmes, Elaine; Cazier, Jean-Baptiste; Nicholson, Jeremy K; Gauguier, Dominique

2016-09-30

The genetic regulation of metabolic phenotypes (i.e., metabotypes) in type 2 diabetes mellitus occurs through complex organ-specific cellular mechanisms and networks contributing to impaired insulin secretion and insulin resistance. Genome-wide gene expression profiling systems can dissect the genetic contributions to metabolome and transcriptome regulations. The integrative analysis of multiple gene expression traits and metabolic phenotypes (i.e., metabotypes) together with their underlying genetic regulation remains a challenge. Here, we introduce a systems genetics approach based on the topological analysis of a combined molecular network made of genes and metabolites identified through expression and metabotype quantitative trait locus mapping (i.e., eQTL and mQTL) to prioritise biological characterisation of candidate genes and traits. We used systematic metabotyping by 1 H NMR spectroscopy and genome-wide gene expression in white adipose tissue to map molecular phenotypes to genomic blocks associated with obesity and insulin secretion in a series of rat congenic strains derived from spontaneously diabetic Goto-Kakizaki (GK) and normoglycemic Brown-Norway (BN) rats. We implemented a network biology strategy approach to visualize the shortest paths between metabolites and genes significantly associated with each genomic block. Despite strong genomic similarities (95-99 %) among congenics, each strain exhibited specific patterns of gene expression and metabotypes, reflecting the metabolic consequences of series of linked genetic polymorphisms in the congenic intervals. We subsequently used the congenic panel to map quantitative trait loci underlying specific mQTLs and genome-wide eQTLs. Variation in key metabolites like glucose, succinate, lactate, or 3-hydroxybutyrate and second messenger precursors like inositol was associated with several independent genomic intervals, indicating functional redundancy in these regions. To navigate through the complexity of these association networks we mapped candidate genes and metabolites onto metabolic pathways and implemented a shortest path strategy to highlight potential mechanistic links between metabolites and transcripts at colocalized mQTLs and eQTLs. Minimizing the shortest path length drove prioritization of biological validations by gene silencing. These results underline the importance of network-based integration of multilevel systems genetics datasets to improve understanding of the genetic architecture of metabotype and transcriptomic regulation and to characterize novel functional roles for genes determining tissue-specific metabolism.

Information-dependent enrichment analysis reveals time-dependent transcriptional regulation of the estrogen pathway of toxicity.

PubMed

Pendse, Salil N; Maertens, Alexandra; Rosenberg, Michael; Roy, Dipanwita; Fasani, Rick A; Vantangoli, Marguerite M; Madnick, Samantha J; Boekelheide, Kim; Fornace, Albert J; Odwin, Shelly-Ann; Yager, James D; Hartung, Thomas; Andersen, Melvin E; McMullen, Patrick D

2017-04-01

The twenty-first century vision for toxicology involves a transition away from high-dose animal studies to in vitro and computational models (NRC in Toxicity testing in the 21st century: a vision and a strategy, The National Academies Press, Washington, DC, 2007). This transition requires mapping pathways of toxicity by understanding how in vitro systems respond to chemical perturbation. Uncovering transcription factors/signaling networks responsible for gene expression patterns is essential for defining pathways of toxicity, and ultimately, for determining the chemical modes of action through which a toxicant acts. Traditionally, transcription factor identification is achieved via chromatin immunoprecipitation studies and summarized by calculating which transcription factors are statistically associated with up- and downregulated genes. These lists are commonly determined via statistical or fold-change cutoffs, a procedure that is sensitive to statistical power and may not be as useful for determining transcription factor associations. To move away from an arbitrary statistical or fold-change-based cutoff, we developed, in the context of the Mapping the Human Toxome project, an enrichment paradigm called information-dependent enrichment analysis (IDEA) to guide identification of the transcription factor network. We used a test case of activation in MCF-7 cells by 17β estradiol (E2). Using this new approach, we established a time course for transcriptional and functional responses to E2. ERα and ERβ were associated with short-term transcriptional changes in response to E2. Sustained exposure led to recruitment of additional transcription factors and alteration of cell cycle machinery. TFAP2C and SOX2 were the transcription factors most highly correlated with dose. E2F7, E2F1, and Foxm1, which are involved in cell proliferation, were enriched only at 24 h. IDEA should be useful for identifying candidate pathways of toxicity. IDEA outperforms gene set enrichment analysis (GSEA) and provides similar results to weighted gene correlation network analysis, a platform that helps to identify genes not annotated to pathways.

miRNA-mRNA integrative analysis in primary myelofibrosis CD34+ cells: role of miR-155/JARID2 axis in abnormal megakaryopoiesis

PubMed Central

Norfo, Ruggiero; Zini, Roberta; Pennucci, Valentina; Bianchi, Elisa; Salati, Simona; Guglielmelli, Paola; Bogani, Costanza; Fanelli, Tiziana; Mannarelli, Carmela; Rosti, Vittorio; Pietra, Daniela; Salmoiraghi, Silvia; Bisognin, Andrea; Ruberti, Samantha; Rontauroli, Sebastiano; Sacchi, Giorgia; Prudente, Zelia; Barosi, Giovanni; Cazzola, Mario; Rambaldi, Alessandro; Bortoluzzi, Stefania; Ferrari, Sergio; Tagliafico, Enrico; Vannucchi, Alessandro M.

2014-01-01

Primary myelofibrosis (PMF) is a myeloproliferative neoplasm characterized by megakaryocyte (MK) hyperplasia, bone marrow fibrosis, and abnormal stem cell trafficking. PMF may be associated with somatic mutations in JAK2, MPL, or CALR. Previous studies have shown that abnormal MKs play a central role in the pathophysiology of PMF. In this work, we studied both gene and microRNA (miRNA) expression profiles in CD34+ cells from PMF patients. We identified several biomarkers and putative molecular targets such as FGR, LCN2, and OLFM4. By means of miRNA-gene expression integrative analysis, we found different regulatory networks involved in the dysregulation of transcriptional control and chromatin remodeling. In particular, we identified a network gathering several miRNAs with oncogenic potential (eg, miR-155-5p) and targeted genes whose abnormal function has been previously associated with myeloid neoplasms, including JARID2, NR4A3, CDC42, and HMGB3. Because the validation of miRNA-target interactions unveiled JARID2/miR-155-5p as the strongest relationship in the network, we studied the function of this axis in normal and PMF CD34+ cells. We showed that JARID2 downregulation mediated by miR-155-5p overexpression leads to increased in vitro formation of CD41+ MK precursors. These findings suggest that overexpression of miR-155-5p and the resulting downregulation of JARID2 may contribute to MK hyperplasia in PMF. PMID:25097177

Using patient lists to add value to integrated data repositories.

PubMed

Wade, Ted D; Zelarney, Pearlanne T; Hum, Richard C; McGee, Sylvia; Batson, Deborah H

2014-12-01

Patient lists are project-specific sets of patients that can be queried in integrated data repositories (IDR's). By allowing a set of patients to be an addition to the qualifying conditions of a query, returned results will refer to, and only to, that set of patients. We report a variety of use cases for such lists, including: restricting retrospective chart review to a defined set of patients; following a set of patients for practice management purposes; distributing "honest-brokered" (deidentified) data; adding phenotypes to biosamples; and enhancing the content of study or registry data. Among the capabilities needed to implement patient lists in an IDR are: capture of patient identifiers from a query and feedback of these into the IDR; the existence of a permanent internal identifier in the IDR that is mappable to external identifiers; the ability to add queryable attributes to the IDR; the ability to merge data from multiple queries; and suitable control over user access and de-identification of results. We implemented patient lists in a custom IDR of our own design. We reviewed capabilities of other published IDRs for focusing on sets of patients. The widely used i2b2 IDR platform has various ways to address patient sets, and it could be modified to add the low-overhead version of patient lists that we describe. Copyright © 2014 Elsevier Inc. All rights reserved.

Program risk analysis handbook

NASA Technical Reports Server (NTRS)

Batson, R. G.

1987-01-01

NASA regulations specify that formal risk analysis be performed on a program at each of several milestones. Program risk analysis is discussed as a systems analysis approach, an iterative process (identification, assessment, management), and a collection of techniques. These techniques, which range from extremely simple to complex network-based simulation, are described in this handbook in order to provide both analyst and manager with a guide for selection of the most appropriate technique. All program risk assessment techniques are shown to be based on elicitation and encoding of subjective probability estimates from the various area experts on a program. Techniques to encode the five most common distribution types are given. Then, a total of twelve distinct approaches to risk assessment are given. Steps involved, good and bad points, time involved, and degree of computer support needed are listed. Why risk analysis should be used by all NASA program managers is discussed. Tools available at NASA-MSFC are identified, along with commercially available software. Bibliography (150 entries) and a program risk analysis check-list are provided.

PICKLE 2.0: A human protein-protein interaction meta-database employing data integration via genetic information ontology

PubMed Central

Gioutlakis, Aris; Klapa, Maria I.

2017-01-01

It has been acknowledged that source databases recording experimentally supported human protein-protein interactions (PPIs) exhibit limited overlap. Thus, the reconstruction of a comprehensive PPI network requires appropriate integration of multiple heterogeneous primary datasets, presenting the PPIs at various genetic reference levels. Existing PPI meta-databases perform integration via normalization; namely, PPIs are merged after converted to a certain target level. Hence, the node set of the integrated network depends each time on the number and type of the combined datasets. Moreover, the irreversible a priori normalization process hinders the identification of normalization artifacts in the integrated network, which originate from the nonlinearity characterizing the genetic information flow. PICKLE (Protein InteraCtion KnowLedgebasE) 2.0 implements a new architecture for this recently introduced human PPI meta-database. Its main novel feature over the existing meta-databases is its approach to primary PPI dataset integration via genetic information ontology. Building upon the PICKLE principles of using the reviewed human complete proteome (RHCP) of UniProtKB/Swiss-Prot as the reference protein interactor set, and filtering out protein interactions with low probability of being direct based on the available evidence, PICKLE 2.0 first assembles the RHCP genetic information ontology network by connecting the corresponding genes, nucleotide sequences (mRNAs) and proteins (UniProt entries) and then integrates PPI datasets by superimposing them on the ontology network without any a priori transformations. Importantly, this process allows the resulting heterogeneous integrated network to be reversibly normalized to any level of genetic reference without loss of the original information, the latter being used for identification of normalization biases, and enables the appraisal of potential false positive interactions through PPI source database cross-checking. The PICKLE web-based interface (www.pickle.gr) allows for the simultaneous query of multiple entities and provides integrated human PPI networks at either the protein (UniProt) or the gene level, at three PPI filtering modes. PMID:29023571

Elastic properties and short-range structural order in mixed network former glasses.

PubMed

Wang, Weimin; Christensen, Randilynn; Curtis, Brittany; Hynek, David; Keizer, Sydney; Wang, James; Feller, Steve; Martin, Steve W; Kieffer, John

2017-06-21

Elastic properties of alkali containing glasses are of great interest not only because they provide information about overall structural integrity but also they are related to other properties such as thermal conductivity and ion mobility. In this study, we investigate two mixed-network former glass systems, sodium borosilicate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)SiO 2 ] and sodium borogermanate 0.2Na 2 O + 0.8[xBO 1.5 + (1 - x)GeO 2 ] glasses. By mixing network formers, the network topology can be changed while keeping the network modifier concentration constant, which allows for the effect of network structure on elastic properties to be analyzed over a wide parametric range. In addition to non-linear, non-additive mixed-glass former effects, maxima are observed in longitudinal, shear and Young's moduli with increasing atomic number density. By combining results from NMR spectroscopy and Brillouin light scattering with a newly developed statistical thermodynamic reaction equilibrium model, it is possible to determine the relative proportions of all network structural units. This new analysis reveals that the structural characteristic predominantly responsible for effective mechanical load transmission in these glasses is a high density of network cations coordinated by four or more bridging oxygens, as it provides for establishing a network of covalent bonds among these cations with connectivity in three dimensions.

["Healthy cities"--requirements and performance. Questionnaire results and a suggestion on quality monitoring (healthy-cities-barometer)].

PubMed

Plümer, K D; Trojan, A

2004-03-01

The overall goal of the WHO Healthy Cities Project was to translate some key points of the Ottawa Charter for Health Promotion (1986) into reality such as public health policies, creating health-promoting environments, strengthening community action through active public participation (empowerment of communities) and equity in health at the local level. These should be anchored within the local political administrative system (PAS), which means health should be on the agenda of policymakers in all sectors. To figure out how far this has been attained after almost 15 years of "healthy cities" policy in Germany was the focal point of the first questioning of local project coordinators. A written questionnaire containing 128 items has been developed in collaboration with the Healthy Cities Network-Coordinator. The questionnaire consists of 78 standardised questions and some (23) open-ended questions for more specific qualitative information. Also included are 27 ten-point rating scales to evaluate the coordinators' view of some aspects of their healthy cities work and to assess its progress. Based on 30 questions of the questionnaire we generated six quality indices, summarised to a quality index for a monitoring model. 47 (90 %) project-coordinators from a list of 52 took part in the first German Healthy Cities survey in the spring 2002. Selected results of the network questioning concerning the local "healthy cities" offices, work priorities and methods demonstrate differences between East and West Germany and general weakpoints of the "healthy cities" projects. Data analysis based on six quality dimensions of the "Healthy Cities" work, Programme Equipment and Commitment (Structure), Concept Quality and Integration within the Network (Process), Self-reported Success and Integration within the City/Municipality (Outcome), revealed some weak points of the " Healthy Cities" work as follows: Basing on the six quality dimensions we present a monitoring model (Healthy-Cities Barometer) which can also be used for strategic controlling (benchmarking) within the German Healthy Cities Network. Based on the data we identified 13 Cities at an A-level (excellent), 22 Cities at a B-level (satisfactory) and 12 Cities at a C-level (INADEQUATE). The "Healthy-Cities Barometer" provides a surveillance instrument which - if constantly used over several years - could offer data for a longitudinal analysis of the Healthy Cities' development. With its help the Healthy Cities Network-Coordinator could gain more information for a better performance and a continuous quality improvement process of the local Healthy Cities projects.

An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize.

PubMed

Wen, Weiwei; Jin, Min; Li, Kun; Liu, Haijun; Xiao, Yingjie; Zhao, Mingchao; Alseekh, Saleh; Li, Wenqiang; de Abreu E Lima, Francisco; Brotman, Yariv; Willmitzer, Lothar; Fernie, Alisdair R; Yan, Jianbing

2018-03-01

Primary metabolism plays a pivotal role in normal plant growth, development and reproduction. As maize is a major crop worldwide, the primary metabolites produced by maize plants are of immense importance from both calorific and nutritional perspectives. Here a genome-wide association study (GWAS) of 61 primary metabolites using a maize association panel containing 513 inbred lines identified 153 significant loci associated with the level of these metabolites in four independent tissues. The genome-wide expression level of 760 genes was also linked with metabolite levels within the same tissue. On average, the genetic variants at each locus or transcriptional variance of each gene identified here were estimated to have a minor effect (4.4-7.8%) on primary metabolic variation. Thirty-six loci or genes were prioritized as being worthy of future investigation, either with regard to functional characterization or for their utility for genetic improvement. This target list includes the well-known opaque 2 (O2) and lkr/sdh genes as well as many less well-characterized genes. During our investigation of these 36 loci, we analyzed the genetic components and variations underlying the trehalose, aspartate and aromatic amino acid pathways, thereby functionally characterizing four genes involved in primary metabolism in maize. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Quantification of Interactions between Dynamic Cellular Network Functionalities by Cascaded Layering

PubMed Central

Prescott, Thomas P.; Lang, Moritz; Papachristodoulou, Antonis

2015-01-01

Large, naturally evolved biomolecular networks typically fulfil multiple functions. When modelling or redesigning such systems, functional subsystems are often analysed independently first, before subsequent integration into larger-scale computational models. In the design and analysis process, it is therefore important to quantitatively analyse and predict the dynamics of the interactions between integrated subsystems; in particular, how the incremental effect of integrating a subsystem into a network depends on the existing dynamics of that network. In this paper we present a framework for simulating the contribution of any given functional subsystem when integrated together with one or more other subsystems. This is achieved through a cascaded layering of a network into functional subsystems, where each layer is defined by an appropriate subset of the reactions. We exploit symmetries in our formulation to exhaustively quantify each subsystem’s incremental effects with minimal computational effort. When combining subsystems, their isolated behaviour may be amplified, attenuated, or be subject to more complicated effects. We propose the concept of mutual dynamics to quantify such nonlinear phenomena, thereby defining the incompatibility and cooperativity between all pairs of subsystems when integrated into any larger network. We exemplify our theoretical framework by analysing diverse behaviours in three dynamic models of signalling and metabolic pathways: the effect of crosstalk mechanisms on the dynamics of parallel signal transduction pathways; reciprocal side-effects between several integral feedback mechanisms and the subsystems they stabilise; and consequences of nonlinear interactions between elementary flux modes in glycolysis for metabolic engineering strategies. Our analysis shows that it is not sufficient to just specify subsystems and analyse their pairwise interactions; the environment in which the interaction takes place must also be explicitly defined. Our framework provides a natural representation of nonlinear interaction phenomena, and will therefore be an important tool for modelling large-scale evolved or synthetic biomolecular networks. PMID:25933116

Pediatric heart failure and worsening renal function: association with outcomes after heart transplantation.

PubMed

Rajagopal, Satish K; Yarlagadda, Vamsi V; Thiagarajan, Ravi R; Singh, Tajinder P; Givertz, Michael M; Almond, Christopher S D

2012-03-01

Renal function deteriorates in some children awaiting heart transplantation. This study was initiated to assess the effects of worsening renal function (WRF) on post-heart transplantation outcomes and to determine the effect of waiting-list associated WRF on survival after heart transplantation. All children aged <18 years who underwent their first heart transplantation between 1999 and 2009, had reported plasma creatinine concentrations at listing and at transplantation, and were free of renal replacement therapy at listing were identified using the Organ Procurement and Transplant Network database. The independent effects of WRF on in-hospital mortality and post-discharge survival were assessed using logistic regression and log-rank analyses, respectively. Of the 2,216 children included in the analysis, WRF occurred in 334 (15%) awaiting heart transplantation: WRF was mild (stage 1) in 210 (63%), moderate (stage 2) in 40 (12%), and severe (stage 3) in 84 (25%). All WRF stages were independently associated with in-hospital, post-transplant mortality: mild WRF with adjusted odds ratio (AOR) of 2.1 (95% confidence interval [CI], 1.2-3.5); moderate WRF, 2.7 (95% CI, 1.1-6.7); and severe WRF, 3.6 (95% CI, 2.0-6.5). WRF was not associated with death after discharge (hazard ratio, 1.2; 95% CI, 0.9-1.7) at a median follow-up of 2.7 years. WRF occurs in 15% of children awaiting heart transplantation and is associated with early but not late post-transplant mortality. Copyright © 2012 International Society for Heart and Lung Transplantation. Published by Elsevier Inc. All rights reserved.

A case analysis of INFOMED: the Cuban national health care telecommunications network and portal.

PubMed

Séror, Ann C

2006-01-27

The Internet and telecommunications technologies contribute to national health care system infrastructures and extend global health care services markets. The Cuban national health care system offers a model to show how a national information portal can contribute to system integration, including research, education, and service delivery as well as international trade in products and services. The objectives of this paper are (1) to present the context of the Cuban national health care system since the revolution in 1959, (2) to identify virtual institutional infrastructures of the system associated with the Cuban National Health Care Telecommunications Network and Portal (INFOMED), and (3) to show how they contribute to Cuban trade in international health care service markets. Qualitative case research methods were used to identify the integrated virtual infrastructure of INFOMED and to show how it reflects socialist ideology. Virtual institutional infrastructures include electronic medical and information services and the structure of national networks linking such services. Analysis of INFOMED infrastructures shows integration of health care information, research, and education as well as the interface between Cuban national information networks and the global Internet. System control mechanisms include horizontal integration and coordination through virtual institutions linked through INFOMED, and vertical control through the Ministry of Public Health and the government hierarchy. Telecommunications technology serves as a foundation for a dual market structure differentiating domestic services from international trade. INFOMED is a model of interest for integrating health care information, research, education, and services. The virtual infrastructures linked through INFOMED support the diffusion of Cuban health care products and services in global markets. Transferability of this model is contingent upon ideology and interpretation of values such as individual intellectual property and confidentiality of individual health information. Future research should focus on examination of these issues and their consequences for global markets in health care.

A Case Analysis of INFOMED: The Cuban National Health Care Telecommunications Network and Portal

PubMed Central

2006-01-01

Background The Internet and telecommunications technologies contribute to national health care system infrastructures and extend global health care services markets. The Cuban national health care system offers a model to show how a national information portal can contribute to system integration, including research, education, and service delivery as well as international trade in products and services. Objective The objectives of this paper are (1) to present the context of the Cuban national health care system since the revolution in 1959, (2) to identify virtual institutional infrastructures of the system associated with the Cuban National Health Care Telecommunications Network and Portal (INFOMED), and (3) to show how they contribute to Cuban trade in international health care service markets. Methods Qualitative case research methods were used to identify the integrated virtual infrastructure of INFOMED and to show how it reflects socialist ideology. Virtual institutional infrastructures include electronic medical and information services and the structure of national networks linking such services. Results Analysis of INFOMED infrastructures shows integration of health care information, research, and education as well as the interface between Cuban national information networks and the global Internet. System control mechanisms include horizontal integration and coordination through virtual institutions linked through INFOMED, and vertical control through the Ministry of Public Health and the government hierarchy. Telecommunications technology serves as a foundation for a dual market structure differentiating domestic services from international trade. Conclusions INFOMED is a model of interest for integrating health care information, research, education, and services. The virtual infrastructures linked through INFOMED support the diffusion of Cuban health care products and services in global markets. Transferability of this model is contingent upon ideology and interpretation of values such as individual intellectual property and confidentiality of individual health information. Future research should focus on examination of these issues and their consequences for global markets in health care. PMID:16585025

MalaCards: an integrated compendium for diseases and their annotation

PubMed Central

Rappaport, Noa; Nativ, Noam; Stelzer, Gil; Twik, Michal; Guan-Golan, Yaron; Iny Stein, Tsippi; Bahir, Iris; Belinky, Frida; Morrey, C. Paul; Safran, Marilyn; Lancet, Doron

2013-01-01

Comprehensive disease classification, integration and annotation are crucial for biomedical discovery. At present, disease compilation is incomplete, heterogeneous and often lacking systematic inquiry mechanisms. We introduce MalaCards, an integrated database of human maladies and their annotations, modeled on the architecture and strategy of the GeneCards database of human genes. MalaCards mines and merges 44 data sources to generate a computerized card for each of 16 919 human diseases. Each MalaCard contains disease-specific prioritized annotations, as well as inter-disease connections, empowered by the GeneCards relational database, its searches and GeneDecks set analyses. First, we generate a disease list from 15 ranked sources, using disease-name unification heuristics. Next, we use four schemes to populate MalaCards sections: (i) directly interrogating disease resources, to establish integrated disease names, synonyms, summaries, drugs/therapeutics, clinical features, genetic tests and anatomical context; (ii) searching GeneCards for related publications, and for associated genes with corresponding relevance scores; (iii) analyzing disease-associated gene sets in GeneDecks to yield affiliated pathways, phenotypes, compounds and GO terms, sorted by a composite relevance score and presented with GeneCards links; and (iv) searching within MalaCards itself, e.g. for additional related diseases and anatomical context. The latter forms the basis for the construction of a disease network, based on shared MalaCards annotations, embodying associations based on etiology, clinical features and clinical conditions. This broadly disposed network has a power-law degree distribution, suggesting that this might be an inherent property of such networks. Work in progress includes hierarchical malady classification, ontological mapping and disease set analyses, striving to make MalaCards an even more effective tool for biomedical research. Database URL: http://www.malacards.org/ PMID:23584832

Satellite image analysis using neural networks

NASA Technical Reports Server (NTRS)

Sheldon, Roger A.

1990-01-01

The tremendous backlog of unanalyzed satellite data necessitates the development of improved methods for data cataloging and analysis. Ford Aerospace has developed an image analysis system, SIANN (Satellite Image Analysis using Neural Networks) that integrates the technologies necessary to satisfy NASA's science data analysis requirements for the next generation of satellites. SIANN will enable scientists to train a neural network to recognize image data containing scenes of interest and then rapidly search data archives for all such images. The approach combines conventional image processing technology with recent advances in neural networks to provide improved classification capabilities. SIANN allows users to proceed through a four step process of image classification: filtering and enhancement, creation of neural network training data via application of feature extraction algorithms, configuring and training a neural network model, and classification of images by application of the trained neural network. A prototype experimentation testbed was completed and applied to climatological data.

Structural integration and performance of inter-sectoral public health-related policy networks: An analysis across policy phases.

PubMed

Peters, D T J M; Raab, J; Grêaux, K M; Stronks, K; Harting, J

2017-12-01

Inter-sectoral policy networks may be effective in addressing environmental determinants of health with interventions. However, contradictory results are reported on relations between structural network characteristics (i.e., composition and integration) and network performance, such as addressing environmental determinants of health. This study examines these relations in different phases of the policy process. A multiple-case study was performed on four public health-related policy networks. Using a snowball method among network actors, overall and sub-networks per policy phase were identified and the policy sector of each actor was assigned. To operationalise the outcome variable, interventions were classified by the proportion of environmental determinants they addressed. In the overall networks, no relation was found between structural network characteristics and network performance. In most effective cases, the policy development sub-networks were characterised by integration with less interrelations between actors (low cohesion), more equally distributed distances between the actors (low closeness centralisation), and horizontal integration in inter-sectoral cliques. The most effective case had non-public health central actors with less connections in all sub-networks. The results suggest that, to address environmental determinants of health, sub-networks should be inter-sectorally composed in the policy development rather than in the intervention development and implementation phases, and that policy development actors should have the opportunity to connect with other actors, without strong direction from a central actor. Copyright © 2017 Elsevier B.V. All rights reserved.

Research on e-commerce transaction networks using multi-agent modelling and open application programming interface

NASA Astrophysics Data System (ADS)

Piao, Chunhui; Han, Xufang; Wu, Harris

2010-08-01

We provide a formal definition of an e-commerce transaction network. Agent-based modelling is used to simulate e-commerce transaction networks. For real-world analysis, we studied the open application programming interfaces (APIs) from eBay and Taobao e-commerce websites and captured real transaction data. Pajek is used to visualise the agent relationships in the transaction network. We derived one-mode networks from the transaction network and analysed them using degree and betweenness centrality. Integrating multi-agent modelling, open APIs and social network analysis, we propose a new way to study large-scale e-commerce systems.

Single-cell resolution of intracellular T cell Ca2+ dynamics in response to frequency-based H2O2 stimulation.

PubMed

Kniss-James, Ariel S; Rivet, Catherine A; Chingozha, Loice; Lu, Hang; Kemp, Melissa L

2017-03-01

Adaptive immune cells, such as T cells, integrate information from their extracellular environment through complex signaling networks with exquisite sensitivity in order to direct decisions on proliferation, apoptosis, and cytokine production. These signaling networks are reliant on the interplay between finely tuned secondary messengers, such as Ca 2+ and H 2 O 2 . Frequency response analysis, originally developed in control engineering, is a tool used for discerning complex networks. This analytical technique has been shown to be useful for understanding biological systems and facilitates identification of the dominant behaviour of the system. We probed intracellular Ca 2+ dynamics in the frequency domain to investigate the complex relationship between two second messenger signaling molecules, H 2 O 2 and Ca 2+ , during T cell activation with single cell resolution. Single-cell analysis provides a unique platform for interrogating and monitoring cellular processes of interest. We utilized a previously developed microfluidic device to monitor individual T cells through time while applying a dynamic input to reveal a natural frequency of the system at approximately 2.78 mHz stimulation. Although our network was much larger with more unknown connections than previous applications, we are able to derive features from our data, observe forced oscillations associated with specific amplitudes and frequencies of stimuli, and arrive at conclusions about potential transfer function fits as well as the underlying population dynamics.

A prior-based integrative framework for functional transcriptional regulatory network inference

PubMed Central

Siahpirani, Alireza F.

2017-01-01

Abstract Transcriptional regulatory networks specify regulatory proteins controlling the context-specific expression levels of genes. Inference of genome-wide regulatory networks is central to understanding gene regulation, but remains an open challenge. Expression-based network inference is among the most popular methods to infer regulatory networks, however, networks inferred from such methods have low overlap with experimentally derived (e.g. ChIP-chip and transcription factor (TF) knockouts) networks. Currently we have a limited understanding of this discrepancy. To address this gap, we first develop a regulatory network inference algorithm, based on probabilistic graphical models, to integrate expression with auxiliary datasets supporting a regulatory edge. Second, we comprehensively analyze our and other state-of-the-art methods on different expression perturbation datasets. Networks inferred by integrating sequence-specific motifs with expression have substantially greater agreement with experimentally derived networks, while remaining more predictive of expression than motif-based networks. Our analysis suggests natural genetic variation as the most informative perturbation for network inference, and, identifies core TFs whose targets are predictable from expression. Multiple reasons make the identification of targets of other TFs difficult, including network architecture and insufficient variation of TF mRNA level. Finally, we demonstrate the utility of our inference algorithm to infer stress-specific regulatory networks and for regulator prioritization. PMID:27794550

Reservoir characterization using core, well log, and seismic data and intelligent software

NASA Astrophysics Data System (ADS)

Soto Becerra, Rodolfo

We have developed intelligent software, Oilfield Intelligence (OI), as an engineering tool to improve the characterization of oil and gas reservoirs. OI integrates neural networks and multivariate statistical analysis. It is composed of five main subsystems: data input, preprocessing, architecture design, graphics design, and inference engine modules. More than 1,200 lines of programming code as M-files using the language MATLAB been written. The degree of success of many oil and gas drilling, completion, and production activities depends upon the accuracy of the models used in a reservoir description. Neural networks have been applied for identification of nonlinear systems in almost all scientific fields of humankind. Solving reservoir characterization problems is no exception. Neural networks have a number of attractive features that can help to extract and recognize underlying patterns, structures, and relationships among data. However, before developing a neural network model, we must solve the problem of dimensionality such as determining dominant and irrelevant variables. We can apply principal components and factor analysis to reduce the dimensionality and help the neural networks formulate more realistic models. We validated OI by obtaining confident models in three different oil field problems: (1) A neural network in-situ stress model using lithology and gamma ray logs for the Travis Peak formation of east Texas, (2) A neural network permeability model using porosity and gamma ray and a neural network pseudo-gamma ray log model using 3D seismic attributes for the reservoir VLE 196 Lamar field located in Block V of south-central Lake Maracaibo (Venezuela), and (3) Neural network primary ultimate oil recovery (PRUR), initial waterflooding ultimate oil recovery (IWUR), and infill drilling ultimate oil recovery (IDUR) models using reservoir parameters for San Andres and Clearfork carbonate formations in west Texas. In all cases, we compared the results from the neural network models with the results from regression statistical and non-parametric approach models. The results show that it is possible to obtain the highest cross-correlation coefficient between predicted and actual target variables, and the lowest average absolute errors using the integrated techniques of multivariate statistical analysis and neural networks in our intelligent software.